116results about How to "Robust" patented technology

The invention belongs to the technical field of carrier frequency offset estimation, and particularly relates to a carrier frequency offset estimation method based on Newton orthogonal matching pursuit. The method comprises the following specific steps of: splitting CFO into two parts of frequencies, namely off-grid deviation and grid point frequency, and further modeling an observation signal as a parameter weighted compressed sensing problem; using a Newton orthogonal matching pursuit algorithm to iteratively optimize the off-grid deviation of the CFO and the estimation of the grid point frequency, and obtaining a CFO candidate frequency set; and obtaining a required CFO estimation result from the candidate set by using the lead code information of the target user. According to the method, the complexity requirement of an actual system is met, meanwhile, the precision of CFO estimation is remarkably improved, and good robustness is achieved.

The invention provides a solid-state laser radar and IMU (Inertial Measurement Unit) robust tight coupling system under the assistance of point cloud intensity, which comprises the following steps of: firstly, pre-processing a solid-state laser radar point cloud by the system, eliminating point cloud defect points, correcting a point cloud intensity value and performing down-sampling; and then geometric feature extraction and intensity feature extraction are carried out on the preprocessed point cloud, and intensity calibration of the laser radar point cloud is carried out. And then compensating the motion of the point cloud by using the high-frequency prior information predicted by the IMU. For geometric and intensity feature point clouds, a classical registration method and a fast plane fitting method are respectively adopted to calculate residual errors, and an intensity feature assisted point cloud residual error measurement model is constructed. And a robust strategy based on an IGGIII robust weight function is designed by using a residual error estimation value in a filtering algorithm. According to the invention, on the premise of keeping relatively low calculation cost, the positioning and mapping capabilities and robustness of the small-view-angle laser radar tight coupling system in a complex environment are improved.

The invention discloses a multi-target detection method based on a multi-source high-frequency track and a high-precision map, which realizes conversion of a video coordinate system, a millimeter wave radar coordinate system and a world coordinate system and fuses a radar target and a video target. The method comprises the following steps: automatically calibrating video and thunder vision; performing automatic deviation correction on a north corner and an equipment position based on multi-straight-line regression; transforming the video sensor into a world coordinate system; and carrying out decision association of the Leiyu tracking target. According to the method, the target trajectory and the high-precision map data are tracked by utilizing the thunder vision high frequency, the complexity of calibration between the sensors and between the sensors and a world coordinate system is reduced, meanwhile, the precision errors of coordinate transformation between the thunder vision sensors and thunder vision data world coordinate transformation are reduced, and compared with the prior art, the method has the advantages that in the application of complex traffic roadside vehicle detection scenes, the detection efficiency is improved. The precision is higher; and the data association has robustness.

The invention discloses an illumination adaptive road surface detection method and system considering small target area identification, and relates to the technical field of intelligent perception. The method comprises the following steps: receiving real-time image data, building a horizon line detection network, and inputting the image into the network to obtain an upper half region image containing environmental elements and a lower half region image containing a road surface and obstacles; the day and night state of the driving scene is judged by using the upper half area image, so that the system automatically adjusts model parameters according to illumination conditions; performing semantic segmentation by using the lower half region image, and intercepting a small-resolution image block with road surface information amount according to a semantic mask; a multi-block fusion decision network is built, blocks are input into the network, and the network can adaptively distribute weights of features of the blocks and perform fusion decision on prediction probabilities of the blocks. According to the invention, the road surface detection is expanded to an all-weather scene, the method has higher practical application value, the identification difficulty of a small target road surface area is overcome, and the accuracy of road surface detection is improved.

The invention discloses a heavy duty gas turbine intelligent control method integrating error active disturbance rejection control and an improved hyperbolic sine and cosine optimizer. The heavy duty gas turbine has the characteristics of numerous monitoring parameters, strong nonlinearity and high coupling degree. The method is used for solving the problem that the control effect is not ideal when the traditional PID control strategy faces the system. The method comprises the steps of collecting and preprocessing data of the heavy-duty gas turbine, establishing a Wiener model of the heavy-duty gas turbine based on variational Bayesian identification, designing an extended state observer and an error active-disturbance-rejection control strategy, and designing a multi-target operation optimization target function of the heavy-duty gas turbine; and then solving the optimal solution of the decision variable of the heavy duty gas turbine controller by using an improved hyperbolic sine and cosine optimizer. The invention provides a scheme and thought for the intelligent control method of the heavy duty gas turbine.

The invention relates to the technical field of image recognition, and particularly discloses a cargo label recognition method based on intelligent logistics warehouse management, which comprises the following steps: S1, collecting an image in a warehouse by taking a vertex of a three-dimensional grid as a standard point and any standard point as a collection point, and determining a target shape in the image; s2, collecting a to-be-detected image, and determining a to-be-determined shape in the to-be-detected image; determining a standard point corresponding to the to-be-detected image, determining a to-be-compared shape, and determining a comparison shape based on the Euclidean distance between the center of the to-be-compared shape and the center of the to-be-determined shape; and S3, determining the similarity between the comparison shape and the to-be-determined shape, and judging whether the cargo label is an abnormal label or not according to the similarity. According to the invention, the abnormal cargo label is recognized in advance and prompted, so that the inventory management is prevented from being delayed.

The invention discloses a fault classification system and method based on a distributed device DTW method. The fault classification system comprises a knowledge sample module, a data preparation module and a fault classification module. The knowledge sample module is connected with the fault classification module, the knowledge sample module can be updated according to faults provided by the fault classification module through interconnection of the knowledge sample module and the fault classification module, so that the intelligent degree of the knowledge sample module is automatically improved, and the data preparation module is connected with the fault classification module. The knowledge sample module is used for initializing a knowledge sample library and dynamically updating data of the knowledge sample library. The data preparation module is used for signal acquisition and fault detection and positioning. And the fault classification module is used for weighting coefficient calculation, sample similarity calculation, category similarity calculation and classification result determination. According to the method, DTW method similarity calculation is carried out by using fault data and traveling wave current data in a system sample library, the similarity of each fault category is selected by using distributed sensor data results at different positions, and finally, the category with the highest result similarity is determined as the fault type.

The invention belongs to the technical field of industrial process control, and discloses an internet-of-vehicles cooperative vehicle fleet mixed triggering formation control method under network limitation, which comprises the following steps: constructing a longitudinal dynamic model and a formation topological structure of cooperative vehicles to describe a relative relationship between the vehicles, establishing an environment limitation model, and constructing a formation model; the nonlinear state of the cooperative vehicle is observed and estimated through the mixed trigger communication condition; a hybrid triggering mechanism is constructed by using a network quality of service QoS mapping function and a self-adaptive threshold value, so that the problem of complexity explosion caused by error derivation is avoided; and finally, constructing a consistency controller model of the collaborative vehicles, and realizing stable tracking and formation collaboration of the motorcade in a dynamic network environment. According to the invention, the vehicle can still keep efficient and smooth communication and control under the conditions of bandwidth limitation, delay change or data packet loss and the like, the network utilization rate is improved, and stable control of a motorcade is realized under various communication topologies.

An intelligent compensation method for coupling errors of a dynamic gravimeter comprises the following steps: selecting typical environment interference influencing the dynamic gravimeter in a complex measurement environment, and analyzing an influence mechanism of each typical environment interference on the measurement accuracy of the dynamic gravimeter; according to the influence mechanism under each typical environment interference, analyzing a coupling error influence mechanism between the typical environment interferences; based on the coupling error influence mechanism, constructing a coupling error comprehensive compensation model; adding the coupling effect loss into a data-driven loss function, and defining a model coefficient constrained by physical information; and performing model training by using the training data, and calculating the total loss of the verification set on the obtained model to obtain a final coupling error comprehensive compensation model. According to the invention, the coupling error of the dynamic gravimeter in a complex environment is compensated based on coupling error mechanism analysis and a physical constraint long-short-term memory model, and the measurement precision and environmental adaptability of the dynamic gravimeter under complex multi-factor interference conditions are improved.

The application discloses a kind of battery core temperature online estimation and prediction method, system, equipment and storage medium based on mixed TSDM-AMBO-GRU, applied to lithium ion battery core temperature estimation and prediction field, comprising: obtaining battery operating data, and utilizing TSDM to create synthesis of battery operating data, as training set with battery operating data together;Training set is input to BO-GRU-AM framework, and the battery core temperature prediction model based on BO-GRU-AM is obtained by training;Input test set to battery core temperature prediction model, and obtain battery core temperature prediction result.The application not only can effectively overcome the problem caused by uneven distribution of temperature sensors and limited data in lithium ion battery system, and can realize real-time, efficient and accurate battery core temperature prediction under various temperatures and complex conditions, provide reliable fault warning and real-time monitoring support for BMS in practical application.

The invention discloses an information source channel joint coding method for joint digital communication and analog communication. The method comprises the following steps: step 1, in a digital branch, inputting a picture, and firstly performing down-sampling and image coding to obtain a code stream; 2, in the analog branch, subtracting the predicted value from the input picture to obtain a residual error, and performing learning-based transformation on the residual error to obtain a characteristic of the residual error; step 3, bandwidth allocation is realized; 4, sending the characteristics subjected to bandwidth allocation to a receiving end through a wireless channel; 5, at a receiving end, the signals received by the digital branches are restored into predicted values through demodulation, channel decoding, image decoding and up-sampling in sequence; and step 6, performing demodulation and learning-based inverse transformation on the signals of the analog branches, reconstructing a residual error, and adding the residual error and a predicted value to obtain a reconstructed picture. According to the invention, source and channel coding is carried out by using a traditional separated coding method through a digital branch, and transmission is carried out by using a residual error through an analog branch, so that better performance is realized.

The present invention discloses a target direction finding method based on the weighted instantaneous phase difference of a single channel of a vector hydrophone. This method utilizes the characteristics that the line spectrum intensity of an underwater target is 10 to 25 dB higher than that of a nearby continuous spectrum, and that the instantaneous phase difference corresponding to its frequency unit is relatively stable, while the instantaneous phase difference corresponding to the background noise frequency unit changes randomly. The variance of the instantaneous phase difference of each channel frequency unit is weighted to further suppress the energy interference of the background noise, enhance the line spectrum signal-to-noise ratio gain, and achieve high-precision direction finding of the underwater target position. Through the above-mentioned method, the present application utilizes the weighted processing principle of the stability of the instantaneous phase difference of the line spectrum to enhance the line spectrum energy in the sound pressure velocity channel signal of the vector hydrophone, and further improves the target position accuracy by combining the complex sound intensity. The simulation analysis and experimental data processing results prove the effectiveness and good engineering practicality of the processing method.

The invention relates to the technical field of wheel monitoring, in particular to a wheel polygon monitoring method based on an improved self-adaptive wave trap, which can accurately and efficiently represent and quantify wheel polygon characteristics in real time and realize wheel state monitoring. The method is applied to the state monitoring and detection application of the polygon of the high-speed train wheel with harmonic characteristics for the first time. By introducing an adjustable factor into a traditional NG algorithm, compared with a traditional ANF, the improved MANF has a higher convergence speed and still keeps good robustness in a large-noise environment, wheel polygon features can be accurately and efficiently represented and quantified in real time, and wheel state monitoring is achieved.

This application discloses a method, system, and storage medium for controlling the charging power of an electric vehicle. The method includes: acquiring the target charging completion time and target charging amount set by the user, as well as the current battery charge; calculating the remaining charge required and the remaining available charging time, wherein the remaining available charging time deducts the reserved buffer time, the derating time in the high charge range, and the safety margin time based on the battery state; determining the target average charging power for the next cycle based on the ratio of the remaining charge required to the remaining available charging time; and comparing the actual charge with the expected charge after the time cycle of each charging process. If there is a deviation, the target power for the next cycle is dynamically corrected bidirectionally based on the magnitude of the deviation and the urgency of the remaining time, ensuring that the corrected power does not exceed the safety limits of the battery and the charging pile. This application achieves precise matching between the charging process and the user's time needs, improving charging efficiency and user experience.

The invention discloses an image watermarking algorithm based on Kyber fully homomorphic encryption, which is characterized in that an anti-quantum Kyber lattice cryptographic algorithm is combined with a Patchwork watermarking algorithm, so that the exchangeability (first encryption and then embedding or first embedding and then encryption) of an encryption and watermark embedding sequence is realized, and dual-mode watermark extraction of a ciphertext domain and a plaintext domain is supported. According to the method, the addition homomorphic characteristic of Kyber is utilized, it is ensured that the operation sequence does not affect ciphertext generation and watermark extraction, the safety defect of a traditional algorithm in the quantum environment is overcome, and the method is suitable for scenes of digital copyright management, medical data sharing and the like and has the advantages of quantum attack resistance, high robustness, outstanding privacy protection capacity and the like.

The invention relates to a control device for a disconnector, comprising an electric motor for driving the on-off of the disconnector, the disconnector being switched from off to on when the electric motor is rotated in a first direction, the disconnector being switched from off to on when the electric motor is rotated in a second direction, and the disconnector being switched from off to on when the electric motor is rotated in a second direction. The disconnecting switch is switched from connection to disconnection; the current direction switching unit comprises a first power supply end, a second power supply end, a grounding end and a current direction switching switch, under the condition that the current direction switching switch is connected with the first power supply end and the grounding end, the motor rotates in the first direction, and the motor rotates in the second direction; under the condition that the current direction change-over switch is connected with the second power supply end and the grounding end, the motor rotates along a second direction; and the power supply change-over switch is coupled with the isolating switch, the power supply change-over switch is connected with the second power supply end after the isolating switch is switched on, and the power supply change-over switch is connected with the first power supply end after the isolating switch is switched off.

The present invention provides a method for coordinated voltage control of AC / DC distribution network partitions, including establishing an AC / DC distribution network voltage control model; partitioning the AC / DC distribution network; modeling the voltage control problem after partitioning as a state-adversarial Markov decision process; solving the state-adversarial Markov decision process; interactively training an attacking intelligent agent and a defensive intelligent agent; and deploying the trained defensive intelligent agent online. The present invention solves the problem of coordinated control of multiple devices in an AC / DC distribution network, improves the coordination of multiple controllable devices, and at the same time considers the uncertainty of the observed state, improves the robustness of the control method, and achieves a better voltage control effect.

The invention relates to the field of insurance claim settlement, in particular to an intelligent contract-driven insurance claim settlement automation system. The method comprises the following steps: constructing an original data matrix based on collected claim settlement data and non-claim settlement data, and carrying out decentralization and data standardization processing to obtain a standardized data matrix; constructing an adaptive logical reasoning tree model based on the standardized data matrix of the claim settlement data, and generating an output vector of an adaptive logical reasoning tree node; the condition threshold matrix is adjusted, the rule set matrix is evolved, then the total amount of claim settlement is calculated, and the adaptive logical reasoning tree model is evaluated and optimized; and calculating a final total amount of claim settlement based on the standardized data matrix of the non-claim settlement data. The problems that the rule set updating and model optimization process is rigid, and the flexibility and adaptability of claim decision making are insufficient are solved; data standardization and feature extraction lack robustness and accuracy; when a system of a fixed rule set processes multi-dimensional and high-complexity requests, decision deviation occurs.

This invention discloses a preventative voltage control method for grid-connected energy storage based on voltage sensitivity, comprising the following steps: updating the voltage sensitivity matrix online based on real-time operating data of the distribution network and predicting future photovoltaic output curves; determining whether there is a voltage limit exceeding situation at future nodes based on the voltage sensitivity matrix; if there is a voltage limit exceeding situation at future nodes, calculating the active power required by the grid-connected inverter based on the voltage sensitivity matrix and photovoltaic output, and generating a charging curve; adaptively adjusting the charging curve based on the real-time state of charge of the energy storage, and charging the grid-connected inverter before the voltage limit exceeds the limit. The beneficial effects of this invention are: changing the voltage support mode of the energy storage module in the grid-connected energy storage system from passive response to active prevention; when the system's reactive power capacity is insufficient, pre-charging the energy storage allows for sufficient safety margin for the system voltage during critical future periods and maximizes the absorption of photovoltaic power, reducing curtailment.

The invention discloses a sludge age self-adaptive regulation and control method and system based on dissolved oxygen trend recognition. Aiming at the problem of impact response lag caused by difficulty in COD on-line measurement, the method comprises the following steps: under the condition of stable water inlet and aeration, filtering and sliding window feature extraction are performed on an on-line DO signal to obtain a regression slope representing the change of DO along with time, and COD rising impact is reliably identified in combination with an ORP persistence criterion. A mechanism and machine learning fusion model is adopted to determine an identification threshold value and a target sludge age SRT, the sludge discharge amount is rapidly adjusted after impact triggering, the treatment capacity is synchronously matched, and aeration is used for assisting in maintaining DO stable. The system integrates an online monitoring module, a DO recognizable interval judgment module, a feature calculation module, a load recognition module, an SRT decision module and a sludge discharge execution module. According to the method, rapid impact recognition and closed-loop regulation and control can be realized without an online COD instrument, and the impact resistance and the operation stability of the process are remarkably improved.

The application discloses a kind of active control method, device and car of automobile interior noise combined with virtual sensing.The method can include: for the interior noise of vehicle at different speeds, by reference signal, physical monitoring signal and virtual error signal respectively construct multiple groups of auxiliary filter containing optimal control filter information and observation filter containing the transfer function between physical monitoring point and virtual error point;By mean method, construct composite observation filter;At different speeds, based on least mean square estimation error matching mechanism, by reference signal, physical monitoring signal, auxiliary filter, composite observation filter, active noise control is carried out at noise reduction target position.The present application can significantly reduce the noise at ear at different speeds while the arrangement position of error microphone does not affect the normal activities of passengers, improve the comfort of riding.

The present application relates to a kind of angle flicker noise preprocessing methods based on adaptive amplitude suppression, comprising the following steps: obtaining the angle measurement data sequence of current batch, based on the target position estimation value and speed prediction value of last time, the target position prediction value of current time is calculated;Deviation calculation is carried out to angle measurement data sequence and target position prediction value, and deviation sequence is obtained;Adaptive amplitude suppression processing is implemented to the deviation sequence, specifically including: setting amplitude threshold, identifying large value component and small value component in deviation sequence;Large value component is scaled nonlinearly, and its amplitude is compressed to the level close to small value component, while keeping small value component unchanged;After amplitude suppression processing, the deviation sequence is added to target position prediction value, and the modified measurement sequence is obtained;Mean filtering is carried out to the modified measurement sequence, and the preprocessing result is output, and the preprocessing result is input to tracking filter, and is used to update target state estimation.

The motion quality evaluation method based on motion perception and double-flow space-time graph convolution relates to the motion quality evaluation field, solves the problems that the existing rehabilitation motion quality evaluation method is difficult to accurately model the cooperation between joints, the fixed joint grouping strategy is not flexible enough, the model has insufficient recognition of the detail differences of complex rehabilitation motions, and the reliability of the evaluation result is affected, a dynamic joint grouping strategy based on motion amplitude driving is provided, a double-flow STGCN architecture is designed, the position and orientation information of the joints are processed respectively and then fused, a two-stage self-attention module SADG is developed, the inter-group time sequence mode and the intra-group spatial relationship are modeled in stages, and multi-granularity feature interaction fusion is realized. The attention mechanism introduces a constraint guided by the motion amplitude, so that the attention weight is more interpretable and has physical meaning.

The application discloses a kind of based on three-dimensional voxelization map small unmanned aerial vehicle fine inspection path planning method, system, setting and medium, it is related to unmanned aerial vehicle control technical field, the method includes: S1: three-dimensional voxelization modeling is carried out to inspection object and environment, and safety inflation processing is carried out to obstacle;S2: the original inspection view point set is clustered and clustered, and the view point in clustering cluster is sorted according to S type path order;S3: the three-dimensional A* algorithm of optimization is used to generate collision-free polyline path;S4: the line path generated in step S3 is smoothed using line-of-sight algorithm, removes redundant node, generates smooth flight trajectory;S5: the path point after smoothing is converted from local model coordinates to WGS84 latitude and longitude coordinates using decoupling fitting strategy based on control point, generates the GPS waypoint sequence executable by unmanned aerial vehicle.The method provided by the application can solve the problems of unsafe path planning during inspection, low inspection point traversal efficiency, non-smooth flight path and the like in the prior art.

This invention discloses a fault detection and fault-tolerant control method for roll-to-roll systems, belonging to the field of industrial printing control. This method solves the problem of registration error propagation caused by actuator failure. Its technical solution is based on a coupled dynamics model established by fully decoupled proportional-derivative control, and designs a fault detection index based on the 2-norm to identify and locate faulty units in real time. Then, upstream and downstream collaborative fault-tolerant control is implemented: adaptive feedback adjustment combined with gain scheduling is used for the upstream faulty unit, and control law reconstruction that removes the dependence on coupling compensation for the faulty unit is used for the downstream faulty unit to block the error propagation path. This method can effectively suppress error propagation under fault conditions and improve the system control accuracy and robustness.

The application provides a self-adaptive adversarial training method for dynamic visual cabinet recognition, comprising the following steps: S1, initializing target network parameters or initializing target network pre-training configuration, obtaining X clean correctly recognized and not disturbed in a dynamic visual cabinet; S2, generating an adaptive adjustment attack parameter vector theta by using a heuristic differential evolution algorithm of a strategy generator according to the robustness of the target network; S3, inputting the attack parameter vector theta into an adversarial sample generator, generating an adversarial sample by adding disturbance in the X clean ; S4, inputting the X clean and the adversarial sample into the target network for training, and setting a training target function; S5, repeating steps S2-S4 until the maximum iteration number is reached, and obtaining a recognition model for dynamic visual cabinet recognition. The application can improve the adversarial attack capability of the recognition model in the dynamic visual cabinet.

The application discloses a personalized picture retrieval method in a federated learning scenario. It includes: 1) loading a public picture-text pair dataset to generate a model training dataset; 2) based on the text information in the dataset in step 1), the tokenizer word segmentation tool is used to obtain the mapping relationship between words and Token positions; 3) based on the picture information in the dataset in step 1), the picture tensor is obtained after preprocessing; 4) a unified model is constructed based on the pre-training model CLIP; 5) the unified model is trained using the text and image expressions obtained in steps 2) and 3); 6) image retrieval is performed using the unified model trained in step 5), and pictures consistent with the query text are obtained. The application designs a private retrieval database for the federated learning client, integrates client-specific information into the pictures and text, and solves the problems of retrieval accuracy decline and slow convergence caused by the non-independent and identically distributed characteristics of data in the federated learning scenario.

The invention discloses a multi-source single-output green light beacon laser for space application, which is characterized in that a light source part comprises two butterfly-shaped packaging laser devices which are cold backups for each other, the butterfly-shaped packaging laser devices are solid laser devices packaged in butterfly-shaped shells, each butterfly-shaped packaging laser device comprises a semiconductor pumping chip, a shaping optical fiber, a laser crystal Nd: YVO4 and a frequency doubling crystal PPLN, and green light of 532nm is generated; in the filtering and beam combining light path part, 532nm green light emitted by each light source is respectively provided with a half-wave plate for adjusting the polarization direction, is combined into the same light path through a polarization splitting prism, is filtered by a light filter, enters a multimode optical fiber through an optical fiber collimator, and is divided into two paths through an optical fiber coupler; one path is used for monitoring the output power and health state of the laser in real time, and the other path is used as main beacon light. The problem of performance reduction caused by the overheating phenomenon of the light-emitting unit is effectively solved, high-power output can be kept for a long time, and meanwhile the overall light weight and flexibility of the laser are considered.

The application discloses a kind of LDPC multi-bit quantization hardware decoding method suitable for high-speed communication, it is related to the field of communication physical layer digital signal transmission, including the steps 1) reset decoding module, from channel obtains the information sequence to be decoded and carries out suitable bit quantization extension;2) to meet the engineering demand of super high speed, low resource consumption, low latency, the application adopts a kind of full parallel decoding structure, the full parallel decoding structure can realize all check nodes update simultaneously and provide to all variable nodes.3) check node update is carried out by 6 parallel ways, the normalization factor used in the application check node update is obtained by adaptive mode;4) the check node information obtained in step 3 is as the input of variable node update module, variable node update is carried out by 6 parallel ways, the input in the application variable node update module is improved by expanding the number of bit quantization to improve the decoding ability of decoder.

The application relates to a distributed transaction consistency guarantee method based on an Outbox mode, which comprises the following steps: simultaneously writing business data into a business data table and writing a to-be-sent message into an Outbox message table in a local transaction of a business database through a business application and submitting the transaction; performing polling on the Outbox message table at a preset polling period through a message relay service, acquiring the to-be-sent message meeting the condition after adding an exclusive lock and skipping the locked record, sending the to-be-sent message to a message queue and updating the state when the sending succeeds; performing idempotent downstream processing based on a message identifier through a consumption end after querying a consumption record table; in response to sending failure, increasing a retry number and performing next-time retry scheduling, and when the retry number reaches an upper limit, migrating the to-be-sent message to a dead letter table. The application has the advantages of guaranteeing atomicity of business data and message persistence, supporting multi-instance concurrent safety, guaranteeing idempotency of a consumption end and controllable retry scheduling.