158 results about "Fusion system" patented technology

The invention provides a vehicle-road cloud integrated multi-network integration system data classification and grading method, which realizes automatic data screening and marking through construction of a multi-scene data identification rule base and business process feature analysis, and solves the problem of standardized identification caused by lack of a unified classification framework of multi-source data. Semantic relation systematic modeling is achieved by means of a multi-layer architecture model and multi-layer model construction, and the problems of insufficient vehicle and road cloud cross-domain entity semantic abstraction and model fragmentation are solved; according to the method, quantitative evaluation of importance and sensitivity is achieved in combination with regulation requirements and modeled data, the problems that data classification and grading standards are missing and a safety evaluation system is imperfect are solved, a closed-loop process of data recognition, semantic modeling, model mapping and grading evaluation is formed, and the problems that in the prior art, a static rule is relied on, and safety evaluation is poor are solved. And changes of data types, interaction types and security requirements in a multi-network fusion scene cannot be dynamically adapted.

The invention discloses a multi-energy fusion system cooperative scheduling method and device in a port dynamic scene, and relates to the field of port energy system optimization scheduling, and the method comprises the steps: constructing a dynamic coupling relation model according to port data; according to the energy system power of each area at the current time point, a multi-objective optimization model is constructed, and objective functions of the multi-objective optimization model include operation cost minimization, total carbon emission minimization, energy storage equipment service life maximization, energy storage equipment power optimization and energy storage equipment power optimization. The constraint conditions of the multi-objective optimization model are power balance, energy storage charge state, electric hydrogen equipment capacity, berth distribution continuity and load demand priority; according to the multi-target optimization model and the port data of each region at the current time point, determining a target collaborative scheduling operation strategy of each region at the current time point, the target collaborative scheduling operation strategy comprising a multi-energy output distribution scheme, a load response instruction and an equipment operation parameter; and executing the target collaborative scheduling operation strategy of each region at the current time point.

The invention discloses a hydropower station computer monitoring operator station fusion system, which comprises a controlled plant computer monitoring system and an operator station fusion system, and is characterized in that a fusion operator workstation is directly connected with a local switch and a controlled plant switch through double independent network interfaces; a man-machine interface module is fused to uniformly manage monitoring and control of cross-plant equipment; and the data server and the switch adopt a dual-computer redundancy architecture and STP / LACP link redundancy, and are combined with AES-256 encryption and instruction bidirectional verification to improve the security. The system fuses multi-source data through an improved adaptive weighted Kalman filtering algorithm, predicts an equipment state trend by using an LSTM model, supports local / controlled priority mode switching, and automatically triggers data caching and instruction degradation when a network is abnormal. An original system does not need to be transformed, through physical direct connection and logic fusion, the framework is simplified, the operation and maintenance cost is reduced, efficient integration and reliable redundancy of multi-plant monitoring functions are achieved, and the system is suitable for large hydropower stations and one-plant multi-station scenes.

The invention discloses an FME-based adjacent pattern spot fusion method and system, and relates to the technical field of adjacent pattern spot fusion, and the method comprises the steps of data processing, parameter setting and rule configuration, adjacent pattern spot fusion execution, result verification and output and feedback and optimization, fusion standard and rule determination, index system unified evaluation, and spatial relationship optimization processing. Manual intervention is reduced through the automatic working process, and the processing efficiency is improved; the invention further provides an adjacent pattern spot fusion system based on FME, the adjacent pattern spot fusion system comprises a data preprocessing module, a data input module, a parameter setting and rule configuration module, a comprehensive correlation index calculation module, a pattern spot fusion module and a result verification and output module, and the adjacent pattern spot fusion method based on FME is executed.

The invention discloses a role playing model fusion system and method based on retrieval and reflection, and belongs to the technical field of natural language processing. The implementation method comprises the following steps: 1, performing data cleaning on original role historical dialogue data, and performing semantic screening by using semantic similarity to form historical dialogue context data; 2, event knowledge associated with the roles is constructed through association degree matching; 3, constructing a role reflection strategy mode by using historical dialogue data, and generating role reflection data; 4, when a user inputs a question, replying by adopting a multi-source fusion mode based on role thinking; compared with the prior art, in a multi-scene task, a dynamic retrieval role knowledge base is utilized to screen task related background knowledge, and a thinking mode modeling framework based on a role reflection mechanism and a context fusion strategy are constructed to generate high-quality answers conforming to the context; and thus, the fusion ability of the role playing model is improved, and the consistency of role words and language styles is realized.

The invention discloses a configuration processing method and device of a hyper-converged system, a storage medium and electronic equipment, and relates to the technical field of computer hardware, and the method comprises the steps that specified configuration information of a server is acquired, and the specified configuration information is configuration information of a basic input and output system of the server; the specified configuration information is analyzed, actual configuration values of a set of specified configuration items are obtained, and one specified configuration item in the set of specified configuration items corresponds to one function provided by the hyper-converged system; in a set of specified configuration items, under the condition that at least one configuration item with the actual configuration value inconsistent with the expected configuration value exists, the actual configuration value of the at least one configuration item is modified, and therefore the difference between BIOS configuration and the hyper-converged system requirement can be automatically detected and corrected; the configuration processing method of the hyper-converged system in the related technology has the problems of low deployment efficiency and poor reliability caused by high deployment complexity.

The invention discloses a self-adaptive synchronization method, system and platform for a multi-projector wiring-free splicing fusion system based on wireless communication. The method comprises the following steps: generating and acquiring first data corresponding to projectors; wherein the first data is state parameter data of the projector and at least comprises brightness data, color temperature data and picture size data; determining to generate second data corresponding to the first data, and generating corresponding third data based on the second data; wherein the second data is projector state parameter change data; the third data is verification code data; based on wireless communication and in combination with the third data, the second data is dynamically adjusted in real time, and the working states of all the networked projectors are synchronously processed, so that rapid, accurate and self-adaptive synchronization of the states of the multiple projectors under the condition of no wiring is achieved, and the system and the platform are convenient to use. And parameters such as brightness, color temperature and size of the spliced picture are consistent.

The invention discloses an SVG valve hall multi-source monitoring data fusion method and fusion system, and belongs to the technical field of power system equipment monitoring, and the method comprises the steps: carrying out the abnormal value and missing value data cleaning of initial data, outputting the preprocessed monitoring data, carrying out the algorithm matching of the preprocessed monitoring data to complete the time-space unification, and carrying out the fusion of the SVG valve hall multi-source monitoring data. Extracting associated features, forming a multi-source feature parameter set, quantifying data source reliability differences and locking key features by taking the multi-source feature parameter set as a reference, forming a dynamic fusion weight distribution scheme and key feature data, calling the multi-source feature parameter set, and eliminating feature conflicts; and generating a comprehensive fault diagnosis result and a health state evaluation index of the valve hall equipment, outputting early warning information and maintenance decision suggestions, and completing the whole data fusion closed-loop application. And a more efficient monitoring scheme is provided for safe operation of valve hall equipment.

The invention relates to the technical field of brain-computer interfaces, and particularly discloses a fusion system combining a brain-computer interface with transcranial electrical stimulation and a feedback stimulation method. The fusion system comprises a main machine part, an auxiliary machine part, a PCB substrate, a terminal integrated receiver and a feedback calculation module. The host part comprises an electroencephalogram signal acquisition device and a transcranial electrical stimulation device which are both installed on a PCB substrate. The auxiliary machine part comprises an MCU and a first wireless device which are both installed on the PCB substrate. The auxiliary machine part further comprises a battery which is connected to the MCU, the electroencephalogram signal collecting device and the transcranial electrical stimulation device. The terminal integrated receiver has a second wireless device. And the terminal integrated receiver is connected to the feedback calculation module. According to the fusion system, the electroencephalogram signal acquisition device and the transcranial electrical stimulation device are combined to acquire brain waves and feed back and adjust transcranial electrical stimulation parameters, so that nervous excitability can be better induced, and an electroencephalogram value is enhanced.

The invention relates to the technical field of deep mineral exploration, and discloses a deep metal mine multi-source geophysical data real-time fusion system. The system comprises a data access module which divides detection dimensions according to physical field types so as to receive original data; the space-time registration module is used for establishing mapping between original data and a unified space-time reference system through timestamps and space coordinates; the feature extraction module is used for extracting key features from the registration data, determining weights according to physical meanings and constructing a feature association network; the fusion decision module identifies an abnormal value and adjusts a network topology structure based on the credibility of the network evaluation data; and the real-time updating module is used for optimizing the fusion priority and algorithm parameters and generating a real-time fusion result library. According to the system, real-time fusion of multi-source geophysical data is realized, and systematicness and timeliness of data processing are improved.

The invention provides a communication and inductance integrated fusion system, an index determination method, electronic equipment and a medium, and relates to the technical field of communication, the communication and inductance integrated fusion system comprises a fusion base station, a preset terminal and a fusion server, the fusion base station is provided with a passive Internet of Things module, and the preset terminal is provided with an RFID tag; the fusion base station is used for sending a first signal and receiving a second signal through the passive Internet of Things module, the first signal comprises a first sensing signal and an RFID excitation signal, and the RFID excitation signal multiplexes a waveform and a time slot resource of the first sensing signal and sends the second signal to the passive Internet of Things module; the second signal comprises a second sensing signal obtained after the first sensing signal is reflected by the preset terminal and an RFID uplink signal obtained after the RFID excitation signal is backscattered by the RFID tag; and the fusion server is used for performing fusion calculation according to the received second sensing signal and the RFID uplink signal so as to determine a sensing performance index. The perception performance of the system can be evaluated more comprehensively and accurately, and the accuracy of perception performance indexes is improved.

The invention discloses a nine-axis linkage intelligent welding process optimization method based on analogue simulation and digital twinning. An existing welding process mostly depends on artificial experience and single equipment control, and an integrated processing system of simulation prediction, equipment cooperation, virtual-real linkage and iterative optimization is lacked. According to the nine-axis linkage intelligent welding process optimization method, a platform is built based on simulation software, after a three-dimensional model of a to-be-welded component is built, the three-dimensional model of the to-be-welded component is subjected to multi-physics field coupling simulation processing to obtain welding data, the welding data is input into an AI multi-target optimization algorithm to form a simulation data training model, and the simulation data training model is used for training the to-be-welded component. Screening according to the simulation data training model to obtain a processing process of an optimal welding sequence and process parameters; through deep integration of intelligent equipment integration, technological process simulation optimization and digital twin control, the problems of low efficiency, poor quality and large deformation in a traditional manufacturing mode are systematically solved.

The invention relates to the technical field of data processing, in particular to a cleaning fusion system for urban traffic multi-source heterogeneous data, which comprises a space-time correlation graph construction module used for creating a unique node identifier for each GPS data record, roadside camera data record and coil data record according to multi-source heterogeneous traffic data, and establishing a spatial adjacent relation edge by judging whether road segment identifiers to which multiple nodes belong are the same or not. According to the method, context awareness evaluation of data source reliability is achieved, meanwhile, when traffic time series data are processed, the data are decomposed into a low-frequency approximation coefficient representing a long-term trend and a high-frequency detail coefficient capturing a sudden change event, and the approximation coefficients of the multi-source data are fused through the obtained context awareness credibility score; meanwhile, a maximum value selection strategy is adopted for detail coefficients, key signal features caused by real traffic events can be reserved, and the fidelity of fused traffic data is improved.

The invention discloses an adversarial agent-based number-real consistency error adaptive prediction method and system, and belongs to the technical field of information physical system and artificial intelligence crossing. According to the method, a destructive agent for maximizing a number-real consistency error and a prediction agent based on a pre-training language model are constructed for continuous confrontation, in the interaction process, the destructive agent intelligently generates disturbance through reinforcement learning so as to explore a weak link of a system, and the prediction agent predicts a disturbance result; after the system obtains the real error, on one hand, a strategy of destroying the agent is awarded and updated, and on the other hand, the real error is utilized to carry out supervised learning type increment fine adjustment on the prediction agent. Through the closed-loop mechanism of double-agent coevolution, the prediction precision and generalization ability of the data-real consistency error can be significantly improved, and the system is endowed with efficient and online adaptive learning ability, so that the reliability and safety of the data-real fusion system can be comprehensively improved.

The invention discloses an energy structure planning method and system based on an entropy flow dynamic model, and relates to the field of comprehensive energy planning, and the method comprises a first model building module which is used for building a decision matrix and a state matrix, and building an evolution model based on a system dynamics principle; the second model construction module is used for constructing a target function which takes system entropy generation as an optimization target and takes policy implementation cost and system orderliness as constraint conditions according to the entropy balance equation and the thermodynamic force-flow relationship, and constructing a maximum entropy generation model based on the target function and an evolution model; and the path output module is used for performing iterative calculation by utilizing an outer layer nested optimization algorithm based on the maximum entropy generation model to obtain an optimal policy combination of each time node in a preset planning period, and outputting an energy planning maximum entropy path. According to the method, system dynamics and an entropy theory are fused, source-network-load-storage full-link interaction is described, and a scientific and reliable benchmark reference is provided for low-carbon transformation of an energy system.

The present invention relates to a spatio-temporal fusion system and method for time-series integration of multimodal data in which numerical data, image data and the like are combined. Provided are the spatio-temporal fusion system and an operating method therefor, the system comprising: a numerical data reception unit for receiving time-series numerical data for a plurality of variables; an image data reception unit for receiving sequentially captured image data; a sequence encoder, which encodes the time-series numerical data so as to generate numerical tokens; an image encoder, which encodes the image data so as to generate image tokens; a time encoder, which encodes data obtained by combining the time-series numerical data and the image tokens, so as to generate first intermediate tokens; a spatial encoder, which encodes data obtained by combining the image data and the numerical tokens, so as to generate second intermediate tokens; and a fusion unit for deriving integrated characteristic data by using the first intermediate tokens and the second intermediate tokens.

The application discloses a multi-radar point cloud weighted fusion system and method based on an entropy weight method, belongs to the technical field of intelligent stereoscopic warehouse perception and point cloud fusion, and aims to solve the problems of low fusion precision, poor real-time performance and unreasonable weight distribution of existing multi-radar point cloud fusion. The method comprises the following steps: synchronously collecting and pre-processing multi-radar point clouds to generate a set; separating dynamic and static points to obtain static point clouds; dividing fusion voxels and detecting changed voxels; extracting features and standardizing; combining prior weights and entropy weight methods to calculate fusion weights; and weightedly fusing to generate a fusion point cloud map. The application can significantly improve the precision and real-time performance of intelligent stereoscopic warehouse point cloud fusion, and provides a reliable three-dimensional perception basis for upper-layer operations of a warehouse.

The utility model relates to a liquid drop fusion system, including liquid drop sorting module and liquid drop fusion module, liquid drop sorting module includes generating portion and sorting portion, the sorting portion outside is provided with detection device and sorting electrode, the detection device is used for detecting positive liquid drop in the pipeline, the sorting electrode is used for sorting the positive liquid drop, and the detection device is used for detecting the negative liquid drop in the pipeline. A positive liquid drop pipeline and a negative liquid drop pipeline are arranged at the downstream of the sorting part, the liquid drop fusion module comprises a fusion part, and a fusion electrode is arranged on the outer side of the fusion part; in order to solve the problem of expanding and re-culturing of piconano-liter liquid drops and overcome the problem that the piconano-liter liquid drops are directly sorted to a 96-pore plate or a flat plate for expanding culture in the prior art, the piconano-liter liquid drops and the micro-liter liquid drops are fused and amplified by combining the characteristics of the micro-liter liquid drops, further expanding culture of cells is realized, and a large number of stable monoclonal groups are formed.

The application discloses a kind of information physical fusion method and system of mechanical equipment health prediction, wherein the method comprises: collecting the working state data of mechanical equipment;Working state data is input to pre-trained information physical fusion system CPS hybrid model, and the health prediction result of mechanical equipment is obtained, wherein CPS hybrid model is obtained according to the fusion of signal processing physical modeling and deep learning data modeling;The health prediction result is mined, and the real-time state of mechanical equipment is evaluated according to the mining result, and the state evaluation result of machine equipment is obtained.The application aims to use the optimized physical modeling method to extract more rich prior knowledge, and then realize the improvement of hybrid modeling accuracy through the optimized data modeling method, which is beneficial to support predictive maintenance activities, so as to realize the monitoring and control of CPS from physical components to network components to physical components of mechanical equipment in network collaborative manufacturing and intelligent factory.

The invention discloses a bridge dynamic deformation monitoring method and system based on multi-mode joint calculation, and relates to the technical field of structural deformation monitoring, and the method comprises the steps: obtaining acceleration data and Beidou / GNSS data obtained through bridge response, and carrying out the parameter transformation; frequency domain parameter transformation and noise parameter solving are carried out on the time domain parameters obtained through parameter transformation; carrying out bridge structure real-time dominant frequency solution on the frequency domain parameters obtained through transformation; according to the frequency threshold value and the noise characteristics of the sensor, carrying out weight distribution on time domain parameters; and performing time domain parameter weight fusion according to a weight distribution result to obtain a bridge dynamic deformation monitoring result. According to the method, weight parameter fusion is carried out by considering the dominant frequency and noise which change in real time, the fusion strategy and parameters are dynamically and adaptively adjusted according to the signal quality, the carrier dynamic characteristics and the sensor error characteristics which change in real time, and the robustness and precision of the fusion system can be maintained under the complex deformation working condition of the bridge environment.

This invention relates to a method and system for mining potential user needs based on hierarchical temporal memory enhancement. First, a dynamic time window hierarchical slicing mechanism is used to decouple the cleaned multimodal user behavior sequence into long-term historical sequences and short-term real-time sequences. A semantically approximate nearest neighbor graph is constructed from the long-term historical sequence, and adaptive community discovery is performed. This is combined with a large language model to generate a high-semantic-density long-term memory abstract representation. Then, a hybrid prompt template integrating system instructions, long-term memory representation, and short-term sequences is constructed to drive the large language model to complete a three-stage thought chain reasoning process: focused denoising, scene instantiation, and function completion, generating a structured reasoning data package. A dual-tower semantic retrieval and scene-constrained filtering architecture is employed to achieve accurate mapping between the reasoning results and the product database, outputting a product list with recommendation reasons. This invention endows the recommendation system with deep logical reasoning and cross-domain association capabilities, improving the accuracy and interpretability of e-commerce recommendations.

The application provides a hybrid large language model modular fusion system, an implementation method and related devices, which comprises the following steps: firstly, receiving a task request and analyzing to generate a task characteristic vector describing the task demand; then, obtaining the ability characteristic vectors of each expert model and calculating the similarity between the ability characteristic vectors and the task characteristic vector to screen a target expert model group to realize accurate matching of the models; secondly, querying the real-time load state of the computing node where the target expert model group is located and dynamically distributing the task to improve the utilization rate of computing resources; then, controlling the target expert model group to perform multi-round iterative collaborative reasoning through a preset cooperation process, taking the output of a previous expert model as the input of a subsequent expert model to strengthen the collaborative linkage capability among the models; finally, performing fusion processing on the intermediate output result to generate a standardized task output result, ensuring the standardization and accuracy of the output result and improving the stability and reliability of the system operation.

The invention provides a virtual-real fusion system for periodontal subbone pocket teaching and a teaching method. The virtual-real fusion system comprises a learning task construction module, a virtual simulation module, an identification module, an entity operation module, a deconstruction module, an image acquisition module, an image processing module and an intelligent analysis module. A course is issued through a learning task construction module, and a user learns the virtual model under the guidance of an identification module; and then under the guidance of the deconstruction module, physical splicing is carried out by utilizing the entity operation module. The system collects operation data of a user in real time through an image processing or sensor technology, and comprehensively calculates a grasp degree score by combining the correct rate and time consumption of the user in the recognition stage and the splicing similarity, hesitation time and taking sequence of the user in the deconstruction stage. According to the system, through a virtuality and reality combined teaching mode, a user can more clearly master the structures of different types of periodontal subosseous pockets, and the learning efficiency is improved.

Digital object fusion techniques and systems are described. In one or more examples, a base object and an adornment object are received and anchor points of the base object and the adornment object are detected by a digital object fusion system. The digital object fusion system then identifies linked anchor points from the anchor points as supporting a link between the base object and the adornment object. A path is fused by the digital object fusion system that defines the base object and the adornment object based at least in part on the linked anchor points. From this, a fused object is generated by the digital object fusion system by propagating visual style data to the path from the base object or the adornment object.

This application provides a crystal oscillator compensation method and apparatus for a cellular positioning and communication fusion system, relating to the fields of communication and positioning technology. After the positioning module and / or communication module are started, this application determines the validity of historical information based on current environmental parameters. If valid, the historical error data is used as the current crystal oscillator error to reduce processing overhead caused by repeated estimation and shorten the preparation time after system startup. If the historical information is invalid and the positioning module is working, the crystal oscillator error is estimated through the communication module. This avoids the high time overhead, high processing complexity, and even malfunction caused by the positioning module directly performing large-scale time and frequency offset scanning within a large error range. This application allows the crystal oscillator error to converge to a smaller range before performing positioning processing, reducing the system's dependence on high-performance crystal oscillators while ensuring positioning and communication performance, which is beneficial for reducing terminal costs and power consumption.

This invention provides a dynamic weighted fusion system and method based on real-time error covariance closed-loop feedback. Addressing the contradiction between underlying physical coupling interference and the need for high-bandwidth dynamic response in non-stationary random environments for large-scale arrays, this invention utilizes a first-order Markov model to quantify the statistical coherence strength of individual observation units. Secondly, it implements physical-layer regularization constraints, eliminating bus capacitance interference and geometric phase deviation through a slope-constrained driving strategy and spatial consistency mapping. In high-frequency sampling environments of 208Hz and above, combined with transient discrimination logic based on full-axis spatial correlation, an analytical solution from a Lagrange optimized functional is used to establish a negative correlation mapping function between weight allocation and the real-time posterior error covariance trace, achieving dynamic gain suppression for non-stationary observation units. This invention achieves optimal fusion of large-scale redundant information while ensuring high-bandwidth real-time response, significantly improving the system's measurement accuracy and robustness.

The application discloses a slope factor fusion method and system, wherein the method comprises the following steps: obtaining a slope factor according to grid DEM data; performing extreme value normalization processing on the slope factor to obtain a normalized terrain factor; performing multi-factor fusion on the normalized terrain factor to obtain a plurality of slope fusion factors; and comprehensively analyzing and evaluating the plurality of slope fusion factors to screen out a target slope fusion factor. The application also discloses a slope factor fusion system. The application aims to obtain a new slope fusion factor according to a slope factor, so as to improve the application limitation of the original slope comprehensive expression factor and solve the problems that the terrain implicit information analysis and mining are not comprehensive and fine enough.

The application discloses a multi-service fusion system based on cloud video. The system is composed of a backstage, a middle stage and a front stage, and realizes comprehensive fusion of cloud video conference. The backstage is based on resources of the CNOOC cloud platform, and constructs an efficient and reliable video conference system, which supports smooth expansion. The middle stage provides rich video conference services, including basic, advanced, development and access, and realizes seamless connection with multi-vendor systems. The front stage faces users, and provides video conference, command and dispatch, collaborative work and other full-scene business applications, and improves intelligent communication and collaboration capabilities through the fusion of multiple services. The overall system is safe and reliable, easy to expand, and meets the remote communication needs in multiple scenes.

The invention relates to a tracking and identification network integrated fusion system of an SAR (Synthetic Aperture Radar) image, which aims at solving the technical problems of poor single-frame identification effect, non-ideal detection generalization, easy loss of tracking and independent identification and tracking, adopts a technical scheme of weighting fusion tracking and identification outside a detection network, and utilizes the advantage of accurately identifying a target position by using a neural network. A detection position is used as an anchor point, a classical tracking method is embedded into neural network reasoning, a tracker does not depend on a scene, feature layer tracking is introduced on a small-scale feature layer, a cross-shaped position coding layer and double-path feedback are designed, and a large amount of data set training is not needed. The technical effects of improving the tracking and recognition robustness, improving the reasoning speed, improving the multi-target tracking and recognition effect, reducing the influence caused by translation and rotation of front and back frames of the image and improving recognition when the signal-to-noise of the SAR image is relatively low are achieved.

The invention provides an integrated multi-sensing fusion system for monitoring the state of a rotating mechanical part, which comprises a multi-source sensing module, a signal processing module and a fusion analysis module, and is characterized in that the multi-source sensing module comprises a plurality of sensing units and is used for collecting multi-dimensional data in the operation process of rotating mechanical equipment; the signal processing module is used for performing preprocessing and analog-to-digital conversion on analog signals acquired by each sensing unit in the multi-source sensing module, the signal processing module comprises a main control unit, and the fusion analysis module comprises a fusion algorithm. The main control unit performs comprehensive analysis and information fusion on data output by each sensing unit through the fusion algorithm, and realizes real-time transmission of a processing result through a communication interface; by integrating a plurality of sensing units, a signal processing module and a fusion algorithm into a whole, deep fusion of hardware and software is realized, and the real-time performance and accuracy of state monitoring of the rotating mechanical part are ensured.