947 results about "Plug and play" patented technology

The invention discloses a laboratory analytical instrument automatic calibration system based on artificial intelligence, and belongs to the technical field of instrument automatic calibration. Comprising the following modules: an intelligent hardware interaction module for realizing plug-and-play of different instruments and accurate conveying of standard substances; the instrument digital twinning module automatically identifies the characteristics of the instrument and simulates the behaviors of the instrument; the multi-mode AI calibration module is used for optimizing calibration parameters and adjusting the calibration process in real time; the environment intelligent compensation module calculates and generates a compensation coefficient in real time, and eliminates the influence of environmental factors on a calibration result; the instrument health management module is used for evaluating the health state of the instrument and predicting the service life of a core component, and realizing conversion from passive maintenance to predictive maintenance; the calibration knowledge graph module is used for realizing automatic extraction, reasoning and application of calibration knowledge through a graph neural network and continuously optimizing a calibration strategy; and the intelligent scheduling and management module is used for generating an optimal calibration plan, coordinating the work of each module and realizing reasonable distribution and efficient utilization of calibration resources.

A passivity-based dual-mode integrated control method for a grid-connected inverter (GCI) is provided. In view of the insufficient robustness of the conventional single-mode GCI in a high-impedance and low-inertia weak grid, and the problem of wideband oscillation of the grid voltage and grid current or even system instability in nonlinear application scenarios such as grid structure / parameter variation, and plug-and-play of the inverter, the dual-mode integrated control method performs modeling on the GCI based on a port-controlled Hamiltonian (PCH) model, thereby obtaining integrated control with a weighted passivity-based feedback control law for the GCI based on a grid-following (GFL) mode and a grid-forming (GFM) mode. Based on the dual-mode integrated control method, the stable operation of the GCI in severe grid conditions with large fluctuation of the impedance, and desirable robustness of the GCI in nonlinear working scenarios can be ensured.

The invention relates to the technical field of data acquisition, in particular to a multi-source heterogeneous bus data acquisition protocol configuration method, which realizes protocol identification and structure analysis of CAN (Controller Area Network), Modbus and Ethernet / IP (Internet Protocol) bus data by dynamically compiling protocol source codes and registering analysis classes, and comprises the following steps of: extracting protocol feature information from a data stream; the method comprises the following steps of: calling a corresponding protocol analysis class to perform recursive analysis, and executing parameter analysis and mapping, in addition, defining a new protocol semantic feature and dynamically generating a protocol analysis plug-in through an XML (Extensible Markup Language) configuration file to realize protocol semantic-level custom extension, adopting source code level dynamic compilation and plug-in design, supporting a new protocol plug-and-play mode, and being high in practicability. System codes do not need to be modified and redeployed, and the flexibility and expandability of the system are effectively improved.

A system of USB communicating camera comprising an integrated USB camera further comprising a USB communicating camera with a sensor, an image signal processor and integrated with a microcontroller having an image processing module, an inference unit, a first USB interface, a flash memory; a host system with a processor, a user interface application and a second USB interface to communicate to and from the USB communicable camera, the system is user configurable for different application specific pre-trained machine learning models. The user interface application is adapted to receive an application specific configuration data. The inference unit is an artificial intelligence inference unit that draws inference on image frames based on an input and the corresponding pre-trained machine learning model. The system deploys edge computing. A firmware residing in the flash memory remains unchanged when different application specific pre-trained machine learning models are loaded in the flash memory.

The invention provides a multi-modal style migration method, system and equipment based on knowledge distillation, a teacher-student model is designed by introducing a knowledge distillation technology, and multi-modal guided style migration can be realized only by using an image data set to carry out one-time training by using a CLIP text image space alignment property. Compared with CLIPStyler, the speed and efficiency are greatly improved, and compared with LDAST, large-scale text image pairing data is not needed, and manpower and material resources are saved. Besides, compared with the fact that both CLIPStyler and LDAST are trained by designing fixed models, a spatial expansion mapping module is designed in the invention, so that the method can be inserted into all traditional image style migration networks to become a multi-modal style migration network, plug-and-play is realized, and the method has excellent adaptability.

The invention discloses a photovoltaic inverter data monitoring plug-and-play method, and the method comprises the steps: constructing a model list supported by a model conversion program for various inverter brands; the initialization information of the acquisition terminal is configured, so that the acquisition terminal can correctly read the type ID and firmware version information of the inverter; establishing a mapping relation between the model ID and the Modbus protocol, wherein the mapping relation at least comprises a register address, a field type, a byte length, a unit and an alarm and state ID description corresponding to a standard object model field; the acquisition terminal reads the type ID and firmware version information of the inverter, and dynamically constructs a Modbus protocol frame according to a physical model demand field after verification of the support of the model library; and after the fields required by the object model are collected, assembling the object model into a Json structure model with a unified standard, and sending the Json structure model to a cloud for analysis and display. The cloud has the capability of remotely updating firmware, the timeliness and accuracy of the system are ensured, user feedback and technical support requests can be collected, and a model conversion program can be continuously optimized and improved.

The invention relates to the technical field of multi-modal image fusion perception and scene understanding, in particular to a plug-and-play prompt-driven visible light-thermal infrared image semantic segmentation method and system, and the method comprises the steps: respectively extracting the feature representation of an input visible light image and a thermal infrared image through a dual-branch LoRA fine-tuning image encoder; converting a segmentation mask generated by the existing visible light-thermal infrared image semantic segmentation model into unified prompt information, including bounding box prompt or point prompt; using a prompt encoder to encode prompt information into prompt embedding; the prompt-based mask decoder fuses the image feature representation and the prompt embedded feature through a spatial channel cross attention mechanism, and generates a final segmentation mask through a classification head; in the training stage, parameterized random disturbance is added to the prompt of the true value mask, and error distribution of the prediction prompt is simulated. According to the method, high-precision semantic segmentation adaptive to various segmentation models can be realized without retraining, and the segmentation robustness in a complex scene is remarkably improved.

The invention provides a computing power scheduling system and method based on a DPU card, the computing power scheduling system comprises a computing network scheduling server, physical servers and a switch, the computing network scheduling server is connected with a plurality of physical servers, each physical server further comprises a management connector, a server management module and a network card, the management connector is used for connecting the DPU card, and the server management module is used for managing the network card. The management connector is connected with the server management chip, and the computing network scheduling server is used for acquiring computing power of each physical server and scheduling the computing power of the physical server through the switch, so that the computing power gateway based on the DPU can be used in a plug-and-play manner, the physical server can be automatically accessed to the computing power network by inserting a DPU card into the physical server, and the operation is convenient. Physical servers are sensed and managed in a standardized mode, various idle computing power resources are managed in a standardized mode, computing power grid connection is achieved, and abundant available computing power resource pools are aggregated.

The invention relates to the technical field of power distribution automation of a power system, and particularly discloses a general operation and maintenance method and system supporting multiple types of power distribution terminals. According to the method, millisecond-level automatic accurate identification of the power distribution terminal is realized through a multi-layer protocol feature fingerprint extraction technology and a weighted dynamic similarity matching algorithm. On the basis of a double-library cooperation mechanism, after equipment identification succeeds, communication parameters, point table mapping relations and operation and maintenance instructions which conform to international / industrial general standards are automatically triggered, loaded and issued. The plug-and-play and zero-configuration deployment of the power distribution terminal is realized, and the point table configuration error rate is reduced to below 1%. And an unidentified equipment self-learning closed-loop process is designed, so that the system can quickly adapt to a power distribution terminal of a new manufacturer, a new number or a new firmware version. And an automatic parameter read-back and verification comparison mechanism after configuration execution forms an operation and maintenance operation closed loop, so that the accuracy of configuration issuing each time and the controllability of the equipment operation state are ensured.

The invention discloses a multispectral image panchromatic sharpening method based on plug-and-play gradient feature guidance fusion, through effective extraction and integration of gradient guidance features (GRAD), excellent recovery results are obtained in the aspects of structural fidelity, detail retention and spectral consistency, and in addition, the method has the advantages of being simple in structure and convenient to use. Gradient feature guidance is fused and designed into a highly flexible plug-and-play method, and the existing architecture can be seamlessly enhanced. In particular, the present invention explicitly models a GRAD by integrating fine spatial details of a high resolution PAN with intrinsic spectral information of an MSI. Meanwhile, an attention mechanism and learnable weighting and residual connection are adopted, and selective aggregation and adaptive fusion of image information are realized, so that the MSI quality is remarkably improved. In addition, the GRAD is systematically analyzed from the aspects of structure, detail and spectrum, and the result is optimized through a multi-objective loss function. In this way, gradient information is fully mined, high-frequency details are captured, cross-modal structure guide alignment is achieved, panchromatic sharpening of the multispectral image is flexibly and efficiently achieved, and the panchromatic sharpening performance is improved.

The invention discloses a shared power utilization method, system, device, equipment and medium, and the method comprises the steps: obtaining first connector information which is used for indicating an identity label corresponding to a power utilization connector inserted into the shared power utilization equipment; the first connector information is generated after the shared electric equipment reads the electric connector through near field communication; authenticating a user account corresponding to the first joint information to generate an authentication result; and generating a control instruction according to the authentication result, and issuing the control instruction, wherein the control instruction is used for indicating the shared electric equipment to perform switching-on and switching-off actions. According to the invention, plug and play of shared electricity can be realized, and the convenience of shared electricity is improved.

The invention discloses a front-end multi-module development method and system based on module federation. The method comprises the following steps: extracting necessary examples, public components and public methods in a front-end project to a public basic module, and constructing a module federated product; decoupling other functional modules, and configuring a module code and a module federation construction entry in the construction configuration file; remote module lists and configuration information are managed in a centralized mode through the project configuration module; executing a construction command to call the project construction module to independently package each module and update the project configuration module; and when the application is started, the project loading module loads the public basic module and the remote function module according to the project configuration module. Compared with an existing Module Federation scheme with application as granularity, independent construction, configuration management and flexible loading during operation are achieved on the module level, dependence on repeated and redundant logic is avoided, module plug and play and version switching are supported, and therefore development efficiency, construction performance and expansibility are improved.

The present invention discloses a stretchable wristband high-density electromyography system for thumb micro-gesture recognition, including a high-density electromyography array and a micro wireless acquisition module; the high-density electromyography array includes three layers of flexible materials, the middle layer of flexible material is printed with flexible electrodes and interconnects, the uppermost and lowermost layers of flexible materials can be removed when in use, and the high-density electromyography array is formed with three parts: a soft skin sensing component, a flexible interconnection, and a rigid pluggable contact pad, wherein the soft skin sensing component is used to closely conformally adhere to the wrist skin, and a flexible electrode is arranged on it, which is electrically connected to the rigid pluggable contact pad through a flexible interconnection, and the rigid pluggable contact pad is a plug-and-play FPC interface for connecting to the micro wireless acquisition module. The system can be directly fitted with the wrist, capture high-fidelity surface electromyography of dynamic and fine gestures centered on the thumb, and apply it to human-computer interaction control.

The invention discloses a high-robustness deep forgery detection method and device based on submerged space adversarial purification, and the method comprises the steps: constructing a robust auto-encoder training frame fusing adversarial attack and a dynamic disturbance mechanism, so as to enhance the robustness of the mapping of a submerged space and an image space; therefore, the original real semantics of the image reconstructed by the auto-encoder can be accurately kept. For different types of adversarial attacks, Gaussian distribution noise is introduced into a submerged space for diffusion, and a submerged vector is gradually restored by using a denoising solver based on a U-Net architecture, so that the purified vector is highly consistent with the original submerged vector, and the adversarial noise in the deep counterfeit content is effectively removed. In addition, the confrontation purifier provided by the invention has a plug-and-play characteristic, does not need to re-train an existing deep counterfeit detector, and shows good generalization ability at the same time.

The invention provides a target detector construction method based on transfer learning in a foggy scene, and belongs to the technical field of deep learning. According to the method, two lightweight neural network modules, namely an image adaptive module and a feature attention enhancement module, are designed according to the requirements of an unmanned aerial vehicle target detector in a foggy scene, and the two lightweight neural network modules are integrated into a plug-and-play image defogging and enhancement network; and then designing a combined target detector network according to the characteristics of the image defogging and enhancing network and various widely used target detectors. According to the invention, the target detector can improve the target detection performance in a foggy scene under the condition that model parameters and computing resources are hardly increased, technical support is provided for reliable visual perception under a severe weather condition, and the method has a wide application prospect.

The invention provides a multi-modal ecological environment monitoring element plug-in integration system and method based on unified objectification modeling. Firstly, an object model and an inheritance system of monitoring equipment, data and an algorithm are constructed; on the basis, a unified logic storage and metadata cataloguing mechanism oriented to heterogeneous databases such as relational databases, non-relational databases and file object databases is designed and realized; the plug-and-play and full-life-cycle management of equipment, data and algorithm models is further realized through a dynamic registration module; common APIs (Application Program Interface) such as object-level addition, deletion, modification and query, space-time association query, concurrent task scheduling and aggregation and the like are externally provided by relying on a unified service bus. And the hybrid storage engine cooperatively manages structured and unstructured data and maintains a topological relation between objects. According to the scheme, object dynamic integration and expansion are completed on the premise that operation is not interrupted, the multi-source heterogeneous data management and cross-modal analysis efficiency is remarkably improved, and the method is suitable for various ecological environment monitoring scenes such as natural reserve, drainage basin pollution supervision and disaster emergency response.

The invention provides an adversarial purification method based on a de-noising diffusion probability model, which comprises the following steps of: gradually adding noise into an input image according to T steps in a forward process of the de-noising diffusion probability model; and step-by-step noise removal is carried out by using a reverse process of the de-noising diffusion probability model and adopting a method matched with a reverse step of the noise adding process, so that a purified image can be obtained. The method is a plug-and-play confrontation purification method and can be directly integrated with an existing deep learning model. In practical application, the method serves as a preprocessing module, the image is purified in the data input stage, and a deep learning model is helped to better cope with countermeasures and attacks. According to the scheme, the structure of the target model does not need to be changed, so that the method has relatively high operability in actual deployment.

The invention is suitable for the technical field of power distribution automation, and provides a dynamic configuration and plug-and-play method and device of power equipment and electronic equipment. The method comprises the steps that after it is detected that access equipment is added, the product type and equipment information of added new equipment are recognized, and equipment IDs are distributed to the new equipment based on the product type and all equipment in an equipment list; and updating the equipment ID and the equipment information corresponding to the new equipment into the equipment list by taking the equipment as a unit, and sending the updated equipment list to the power distribution master station, so that the power distribution terminal and the power distribution master station carry out transmission of corresponding data of the data object of the equipment based on the updated equipment list and a preset model point table. According to the method, the plug and play function of the equipment can be realized, the equipment data (equipment list) between the equipment and the master station can be automatically updated, manual intervention is not needed, and the problems of heavy work, high error rate and low efficiency of manual configuration are solved.

The invention discloses a video question and answer modeling method based on a hierarchical selection framework, which is characterized by comprising the following steps: firstly, preprocessing video data and text data to obtain video clip features, object features, question features, question word features and candidate answer features as input of a video question and answer model; video clip features, video frame features and object features are selected hierarchically from large to small according to the time span and the space span, and then feature fusion with question features is carried out to realize prediction of answers. The method can be combined with different pre-training models for training and fine tuning, and is plug-and-play; video clips, video frames and object features related to problems can be selected hierarchically, key features related to the problems can be extracted, and irrelevant redundant information can be filtered.

The invention discloses a multi-modal sensor abstract description and packaging method and system based on software definition. Firstly, a unified sensor abstract description model based on software definition is introduced, so that hardware independence is realized, and the differences of a bottom-layer multi-mode sensor in the aspects of interfaces, protocols and data formats can be effectively shielded; secondly, abstract packaging of data is achieved through an autonomous information processing module, and high-bandwidth and high-redundancy original data is converted into low-bandwidth and high-value structured information; in addition, by means of automatic registration, discovery, scheduling and control mechanisms of the sensor management control module on sensor resources, the system realizes a real plug-and-play function. According to the invention, by deploying the autonomous information processing modules at various sensor nodes, the original sensing data is preprocessed, and standardized data packaging with semantic consistency is output, so that the operation load of the central controller is reduced, and the information processing efficiency and the system response capability are also improved.

The invention discloses a mirror image detection method based on generalized implicit reflection perception. A generalized implicit reflection perception framework based on visual prompt is constructed. Specifically, a prompt chain generation module is introduced, mirror image area features are sensed through thinking chain reasoning, and mirror image area feature sensing can be achieved even under the condition that no entity exists. The clear visual prompt is fixed or slightly updated at the image level, and the invention provides a prompt updating module based on a gating mechanism so as to realize feature level and semantic perception updating, reduce reflection interference and enhance a prompt chain. In addition, the invention proposes a cue injection module to drive the model to position the mirror. The modules provided by the invention are all plug-and-play. According to the method, the most advanced performance is realized with extremely low calculation complexity on four mirror image references, and the method exceeds single-mode, multi-mode and video-level methods of complete supervision and weak supervision. Good performance is also obtained on seven pieces of glass, camouflage and underwater benchmarks.

The invention relates to the field of attack and defense resisting of computer vision, in particular to a plug-and-play selective module robust resisting fine tuning method, which comprises the following steps of: introducing a generalization sensitivity index and a robust key index of a module, and based on the robust key index and the generalization sensitivity index of each layer of network module contained in an initial model; determining a network module for implementing fine tuning by taking maximization of a robust key index and minimization of a generalization sensitivity index as targets; and finally, performing fine tuning on the parameters of the network module subjected to fine tuning by freezing the parameters of all other modules and utilizing a fine tuning sample set to obtain a robust enhanced image classification model, thereby comprehensively considering the relationship between model robustness and generalization, accurately identifying the most critical module and performing fine tuning, and improving the robustness of the image classification model. The model robustness is greatly enhanced under the condition of keeping or even slightly improving generalization, and the method has a plug-and-play characteristic, can be deployed in various adversarial trainings as a general component, and can perform secondary robustness enhancement on a robust model.

The invention discloses a BLDC (brushless direct current) driving parameter self-tuning embedded system and method for multiple equipment types, and the method comprises the steps: constructing a BLDC unified mathematical model containing an electromagnetic torque equation, a back electromotive force equation and a mechanical motion equation, and building a nonlinear mapping relation library of motor type identification codes and a key electrical parameter set; a predefined multi-mode excitation signal sequence is injected into the to-be-driven BLDC motor, dynamic response data are synchronously collected, and the dynamic response data are used for representing the characteristics of the key electrical parameter set; based on collected dynamic response data, equivalent inductance and equivalent resistance in a key electrical parameter set are decoupled and extracted through a frequency domain impedance analysis method, and meanwhile, a counter electromotive force coefficient and rotational inertia in the key electrical parameter set are identified by combining time domain counter electromotive force zero crossing point detection with rotating speed differential operation. Based on a motor fingerprint feature library and a fuzzy adaptive architecture, multi-model debugging-free plug-and-play is realized, and stable control performance is maintained under a dynamic working condition.

The invention discloses an arbitrary-scale image super-resolution reconstruction method based on local features. According to the invention, two efficient plug-and-play modules are designed and can be combined with an existing fixed-scale super-resolution network so as to realize a super-resolution task of any scale. Wherein the scale perception feature adaptive module (SLFAM) solves the problem of lack of adaptability to the scale and the local structure of an image in the feature extraction process by generating a scale perception feature adaptive dynamic convolution kernel; the local feature adaptive up-sampling module (LFAUM) fuses scale information, projection position coordinates, local features, receptive field offset and other information in the up-sampling reconstruction process to generate a deformable up-sampling convolution kernel, and the function of up-sampling reconstruction of any scale is achieved. The method is mainly applied to the technical field of image super-resolution reconstruction, and has wide application prospects in the fields of remote sensing satellite images, medical images, security monitoring and the like.

The invention discloses a plug-and-play Rydberg atom preparation device based on a three-photon absorption method, which comprises a laser generator, a laser input module, a laser detector, three frequency stabilization modules and a temperature and humidity control module, and is characterized in that the laser generator is used for preparing laser to be measured; the input module is used for transmitting and introducing laser; the saturated absorption frequency stabilization module, the electromagnetic induction transparent frequency stabilization module and the heating electromagnetic induction transparent frequency stabilization module all adopt a glass bonding technology to build frequency stabilization light paths; the laser detection device is used for detecting laser lines in the saturation absorption frequency stabilization module, the electromagnetic induction transparent frequency stabilization module and the heating electromagnetic induction transparent frequency stabilization module and locking the laser frequency corresponding to the specific wavelength. According to the invention, a frequency-stabilized light path is built by using a glass bonding technology, so that devices and the size are greatly reduced, and the integration level of a light path system is greatly improved; moreover, the degree of freedom of device adjustment can be reduced, and the reliability and stability of a laser frequency stabilization optical path are effectively improved.

The invention discloses a token routing enhancement method of a visual language model based on hybrid experts, which is plug-and-play and can realize efficient routing of visual tokens on a model of a pure visual mode based on a hybrid expert architecture or a multi-mode model containing the visual mode. The mode-specific routing strategy enables the method to identify internal distribution of information of different modes, so that token routing of visual and other modes is performed separately. In addition, important tail foreground tokens and redundant head background tokens in vision are distinguished through the probability variance of token routing, and visual information mining is facilitated. And by enhancing the learning of the experts on the important tail foreground tokens in the vision, the important information in the vision can be more efficiently captured and learned. According to the method, the inference parameter quantity is kept unchanged while more advanced performance is realized on the backbone model of the pure visual mode and the multi-mode backbone model containing the visual mode.

The invention discloses a prefabricated temperature measurement system for a sleeve side of an all-insulation ring main unit. The prefabricated temperature measurement system comprises a wireless three-phase temperature sensor, a host module, an Internet of Things gateway and an in-situ monitoring terminal. A sensor probe is directly arranged in an insulating gap between a cable head and a sleeve, is made of a high-temperature-resistant insulating material and is internally provided with an electromagnetic shielding layer, and 2.4 GHz wireless communication is supported. A temperature rise rate analysis algorithm is built in the host module, an early warning mechanism is triggered when the slope k is calculated to be larger than or equal to 0.5 DEG C / h by adopting a least square method, and an environment temperature compensation factor is introduced to correct errors. A factory pre-integration + plug-and-play mode is innovatively adopted, rapid deployment is realized through a DIN guide rail and an anti-misplug aviation plug, and a dual-mode power supply system is matched at the current fault; the low-frequency sampling of the storage battery is automatically switched at 20A, and the wake-up period is dynamically adjusted through PWM. According to the scheme, the problems of large delay of traditional infrared temperature measurement, complex installation of a contact sensor and failure of small load are solved.

The invention discloses an island micro-grid distributed cooperative control method based on local information and a storage medium, and belongs to the technical field of micro-grids, and an island micro-grid system comprises a converter of network construction type control and network following type control. And according to local information, the network tracking type control adopts a maximum power point tracking point tracking (MPPT) algorithm to control power output. The reactive power of the network construction type control parallel converter is output and distributed according to the fixed voltage regulation droop coefficient; and the active power of the network construction type control parallel converter is output and distributed according to the frequency modulation droop coefficient adaptively updated based on local information. According to the method, power instruction distribution of island micro-grid and network type control and network construction type control is generated by local information, instruction distribution of upper-layer centralized control does not need to be carried out, plug and play, flexible reconfiguration and decentralized control of an island micro-grid inverter can be realized, and the method has relatively good practicability.

The invention relates to the technical field of power system automation, and provides a containerized plug-and-play method and system for an edge internet of things device, and the method comprises the steps: laying a northbound protocol module, a message bus module, a data center module and a management center module; the northbound protocol module is deployed at the edge gateway, communicates with the edge cluster through a northbound communication protocol, realizes management control of the edge cluster on the edge gateway, and also realizes a function of transmitting information to the edge cluster by the edge gateway; the message bus module adopts an MQTT message bus to communicate with an application so as to realize data subscription and release; the data center module is used for storing important information of real-time data, historical data and model data, and interacting data of an edge cluster with data of edge equipment; and the management center module is deployed in a host machine and is responsible for managing containers and application programs. According to the invention, the problems of data processing, delay, safety, resource utilization and the like of the existing new energy transformer substation are solved.

The invention relates to the technical field of industrial communication and Internet of Things, in particular to an IO-Link gateway system and method for heterogeneous protocol unification and edge enabling. Comprising a hardware layer, a protocol adaptation layer, a data processing layer, an intelligent computing layer and a communication interaction layer which are connected in sequence to achieve standardized conversion and edge intelligent processing of heterogeneous industrial data, and data time sequence consistency and system operation stability are guaranteed in the whole process. According to the invention, a plurality of heterogeneous industrial protocols are downwards and uniformly mapped to a technical path of an IO-Link international standard, and heterogeneous data are converted into a standard IO-Link object dictionary at a gateway level, so that field devices of different manufacturers and different protocols can carry out data interaction with a uniform and semantic-rich information model; therefore, plug-and-play of data is realized in the equipment access layer, and a solid foundation is laid for constructing an integrated industrial Internet of Things system.