225 results about "Supervisory control" patented technology

The present invention relates to a method for constructing a digital twin system for an additive manufacturing process with lifecycle data management. The digital twin system for an additive manufacturing process constructed by the method includes a data acquisition and supervisory control system, a data management and storage system, a manufacturing executing system, a configuration model, a simulation system, and a multi-physics simulation system. The present invention can fully and accurately characterize the molding quality of parts, thereby saving a lot of time required for offline data processing, and achieving real-time acquisition and updating of data.

A hybrid approach involving the mix of communication patterns and passive fingerprinting is used to identify unknown device types, manufacturers, and models of devices of digital control systems. ANDVI implementation maps the identified devices to their known vulnerabilities. According to one example, to identify how interdependence among existing atomic vulnerabilities may be exploited by an adversary to stitch together an attack that can compromise the system, model-checking based A2G2V is employed. According to another example, an A2G2V algorithm uses existing model-checking tools, an architecture description tool, and code to generate an attack-graph that enumerates the set of all possible sequences in which atomic-level vulnerabilities can be exploited to compromise system security. In yet another example, identification of label-cuts within an attack-graph automatically identifies a set of critical-attacks that, when blocked, renders the system secure. A linear complexity approximation utilizing SCCs helps identify the minimum label-cut representing a critical-attacks set.

The invention belongs to the technical field of electromechanical equipment fault diagnosis, and discloses a wind turbine generator transmission chain online fault diagnosis method, which specifically comprises the following steps: S1, adopting an SCADA (Supervisory Control and Data Acquisition) system to collect environment, electrical and vibration multi-source monitoring parameters of a wind turbine generator in real time and pre-process the parameters, thereby effectively improving the accuracy and availability of data; s2, through the design of a multi-source feature association fusion module, complementarity of environment, electrical and vibration parameters is fully utilized, and the accuracy and reliability of fault diagnosis are improved; s3, a teacher-student network framework is constructed, online fault model construction and real-time diagnosis are achieved, the real-time performance and the intelligent level of fault diagnosis are improved, due to the application of a class balance sampling mechanism and a positive and negative combined learning strategy, the influence of continuous state label offset is eliminated, pseudo label noise interference in online samples is effectively reduced, and the real-time performance of fault diagnosis is improved. And the adaptive diagnosis capability of the model in a working condition environment dynamic change scene is improved.

The invention relates to the technical field of industrial park intelligent monitoring, and particularly discloses a data acquisition and monitoring control method based on an intelligent industrial park, which comprises the following steps: acquiring key state data of equipment in real time, including operation time, operation temperature and operation power; an advanced signal processing algorithm is used for calculating an operation temperature abnormal index and an operation power abnormal index, the system can comprehensively evaluate the state of equipment and accurately judge whether slight or serious abnormal conditions exist or not based on detailed data analysis results, and the system can not only give out instant early warning notifications but also give out alarm information according to the serious abnormal conditions. According to the method, a machine learning model is adopted to predict the future operation state of the equipment, the equipment state abnormal coefficient in each future monitoring period is predicted based on the equipment state data in the current period, and classification and dynamic regulation and control of the equipment state are carried out according to a preset threshold value.

The invention relates to the technical field of supervision control and data acquisition, in particular to an intelligent monitoring system based on a multi-sensor fusion technology, comprising a multi-sensor acquisition and preprocessing module which acquires and self-calibrates at least two kinds of physical quantity data in real time and fuses the physical quantity data into a unified monitoring feature vector; and the fault diagnosis and prediction module is used for integrating interpretable semantic analysis in combination with a production plan and a maintenance record. And performing equipment state diagnosis, operation trend analysis and fault prediction in real time by utilizing electric inspection type monitoring, generating health assessment and early warning, and guiding optimization and adjustment of a control strategy. And the data storage module is used for storing semantic data model evaluation results, diagnosis reports and early warning information, and supporting fault root analysis and control effect evaluation based on processing batches and time sequences. And the remote man-machine interaction interface is used for displaying the equipment running state, the control parameters and the automatic process in real time, supporting voice instruction interaction and facilitating remote monitoring and intervention of an operator.

The invention provides an SCADA system label generation method and system based on structured multi-source information fusion, and relates to the technical field of industrial automation and control. According to the method and the system, firstly, an initial information modeling framework including a tag name, a data type and an equipment association relationship is generated based on an SCADA system architecture; establishing a multi-level constraint rule base according to engineering domain characteristics, analyzing the information modeling framework through a large language model, performing semantic verification in combination with a domain knowledge graph, and generating a structured tag file conforming to a used SCADA (Supervisory Control and Data Acquisition) system; and finally, through an application platform of an SCADA (Supervisory Control and Data Acquisition) system or by constructing a digital twinborn verification platform containing a simulation test environment, carrying out an injection test on the generated tag, and verifying the field integrity, logic consistency and system compatibility of a tag file. According to the method, the large language model can adapt to a specific industrial control scene when processing SCADA system label generation.

The invention provides a controllable SCADA (supervisory control and data acquisition) industrial production control platform based on an industrial internet architecture. The controllable SCADA industrial production control platform comprises a field layer, an edge layer, a communication layer, a cloud / fog computing layer and a data management layer, wherein the field layer is composed of a sensor array, an execution mechanism, a PLC controller and an RTU terminal; the sensor array comprises a temperature sensor, a pressure sensor, a flow sensor and a position sensor, and adopts 4-20mA current loop signal output; the execution mechanism comprises an electric valve, a servo motor and a variable frequency driver, and communicates with the PLC through a Modbus RTU protocol; the PLC controller is provided with a dual-core processor and is provided with 16 digital quantity input / output channels and 8 analog quantity input channels; the RTU terminal is internally provided with a LoRa wireless communication module; the edge layer comprises an edge computing node and a protocol conversion gateway; the edge computing node is provided with an FPGA coprocessor and supports an edge reasoning framework; and multi-protocol conversion is realized through the protocol conversion gateway.

The invention relates to the technical field of vacuum induction heating temperature control, and discloses a vacuum induction heating temperature closed-loop control system integrated with SCADA (supervisory control and data acquisition), which is characterized in that a functional material layer with preset Curie temperature is compounded on the surface of an induction coil, and the absolute value of phase difference is analyzed by collecting voltage and current signals of the coil in real time; according to the invention, through the synergistic effect of the electromagnetic impedance sudden change characteristic of the functional material layer and the phase difference detection mechanism, non-contact accurate control of the phase change critical temperature of the workpiece is realized; and meanwhile, due to the coupling application of the asymmetric micro-pulse waveform design and the dynamic adjustment strategy, the contradiction between thermodynamic response and electromagnetic interference in a vacuum environment is effectively balanced, and the control precision and stability of the system are remarkably improved.

The invention relates to the technical field of industrial data acquisition and processing, and discloses a different industrial data optimal acquisition scheme analysis system and method based on an SCADA system, and the system comprises an industrial data acquisition information processing module, an industrial data acquisition scheme analysis module, and an industrial data acquisition optimal scheme generation module. According to client target industrial data acquisition scheme type information, in combination with an intelligent identification algorithm and industrial data acquisition scheme equipment composition information, industrial data acquisition scheme equipment composition information efficient retrieval is carried out, and equipment information used by different types of industrial data acquisition schemes is efficiently and scientifically analyzed; the industrial application applicability of the SCADA system is improved; the unit price information of the client target industrial data acquisition scheme composition equipment and the cost information of the client target industrial data acquisition scheme are scientifically and accurately counted, the cost information of different types of industrial data acquisition schemes is autonomously measured on line, and the scientificity of the industrial application of the SCADA system is improved.

Disclosed is an explainable method for monitoring a state of a generator of a wind turbine generator system on the basis of a spatio-temporal graph. The method includes: S1: acquiring data collected by a supervisory control and data acquisition (SCADA) system; S2: carrying out data understanding on the SCADA data, selecting features associated with the generator, and carrying out data preparation on the selected feature data, and obtaining valid data; S3: embedding the SCADA data, and forming a directed spatio-temporal graph data sequence; and S4: carrying out modeling of a normal behavior model of the generator on the constructed directed spatio-temporal graph data sequence, computing a full-graph-level residual and a node-level residual, computing a residual through an exponentially weighted moving average (EWMA) control chart method, carrying out full-graph-level state monitoring on the generator, forming a fault information transmission chain relation, and enhancing explainability and robustness of a monitoring result.

The invention, which relates to the technical field of the electric power supervision management and control system, discloses a supervision management and control system based on improvement of the electric power marketing service level, and the system integrates four modules of data acquisition, data analysis, supervision management and control and feedback improvement. Basic information, service requests and service process records of clients are collected through the data acquisition module; the data analysis module identifies problems and bottlenecks in the service process; the supervision and control module comprises a real-time monitoring and early warning system sub-module, a service quality evaluation model sub-module, a process monitoring and optimizing sub-module and the like and can supervise and control the service process in real time, and the feedback improvement module collects customer feedback and service evaluation and continuously improves and optimizes the service. The system also has a self-learning upgrading capability, continuously optimizes the service process through an internal feedback mechanism, improves the service quality, effectively solves the defects of an existing power marketing service system in the aspects of supervision and control, and provides a more efficient and convenient service solution for the power industry.

The invention relates to the technical field of monitoring and data acquisition systems, and discloses an SCADA (supervisory control and data acquisition) system based on a large language model, an implementation method and equipment, and the system comprises a user interaction terminal which receives a natural language instruction input by a user and displays a dynamic user interface; the natural language processing module is used for preliminarily analyzing the natural language instruction to obtain a user intention and key information; the large language model is used for deeply analyzing the user intention and the key information and generating a task description or a task execution plan; the MCP arrangement engine is used for mapping the task description or the task execution plan to a predefined function to obtain executable structured data; and the dynamic UI generator is used for generating a dynamic user interface based on the executable structured data and a preset UI instruction. According to the method, the usability and the data analysis capability of the SCADA system are improved through natural language interaction, and meanwhile, the reliability and the safety of the system are ensured by utilizing an MCP and a predefined function mechanism.

A system includes a message broker that uses a publish / subscribe messaging protocol. An edge gateway operatively couples one or more edge devices to the message broker. The edge gateway receives information from one or more of the edge devices and publishes at least some of the received information to the message broker in a protocol that is compatible with the publish / subscribe messaging protocol of the message broker. A host application is operatively coupled to the message broker and subscribes to at least some of the information published by the edge gateway. The edge gateway is configured to determine an edge gateway connection state and publish the edge gateway connection state to the message broker. The host application is configured to determine a host application connection state of the host application and publish the host application connection state to the message broker.

The invention relates to the technical field of supervision control, in particular to a new energy storage optimization control method and system, and the method comprises the following steps: collecting a grid-connected point voltage amplitude deviation, a frequency deviation and a voltage total harmonic distortion rate, and generating a power grid stress index; according to the method, the multi-dimensional state vector is constructed by collecting the grid-connected point voltage amplitude deviation, the frequency deviation and the total harmonic distortion rate to generate the stress index reflecting the power grid operation pressure, accurate quantitative sensing of the power grid state is achieved, the power grid supporting gain coefficient is dynamically generated according to comparison of the index and the preset threshold value, and the power grid supporting effect is improved. And the total required power to be responded by the energy storage system is adjusted and determined, so that the power support strength is matched with the actual demand of the power grid, and insufficient response or excessive response is avoided.

The invention relates to the technical field of supervision and control, in particular to a polyethylene chlorination reaction control system which comprises a hot-pressing time difference extraction module, a viscosity variable-speed recognition module, a chlorine pressure collaborative trend division module, a response centralized recombination module and a stirring amplitude management and control module. According to the method, a multi-source variable data structure is unified through period numbers, cooperative sections with consistent trend directions are constructed, response feature fragments in a continuous period are recognized by combining fluctuation frequency and adjustment amplitude feature extraction, the behavior boundary of each variable in the time dimension is unified, and the recognition precision of multi-variable abnormal evolution is improved; a regulation and control reference is established through trend classification and strength grading, structured expression and controllability analysis of periodic behaviors are realized, the matching between the regulation rhythm and the variable trend is enhanced, and a regulation and control strategy is enabled to have clear boundary recognition, period tracking and behavior intervention capabilities.

A system for AI-supported cybersecurity and regulatory compliance in energy distribution networks, consisting of: a hardware-embedded data acquisition module configured to intercept, capture, and time-stamp operational data streams and to control data traffic from SCADA (Supervisory Control and Data Acquisition) systems, AMI (Advanced Metering Infrastructure) systems, and energy management systems (EMS) via multiple communication protocols without operational latency; an FPGA-based deep packet inspection unit coupled with the data acquisition module, wherein the FPGA firmware is configured to perform line rate filtering, protocol decomposition and metadata extraction of the acquired data and forwards preprocessed packet data to an AI processing unit; an AI processing unit consisting of a multi-core central processing unit (CPU), a dedicated AI accelerator selected from a graphics processing unit (GPU) or a tensor processing unit (TPU), and a volatile memory buffer; a response orchestration module that is communicatively coupled with network management devices and operations controllers, wherein the response orchestration module is configured to perform automated security and compliance remediation measures, including network isolation of compromised segments, enforcement of protocol encryption, and privilege revocation; and an immutable audit logging subsystem configured to record all detected events, compliance assessments, and corrective actions in a blockchain-based distributed ledger, with each log entry cryptographically anchored with a secure hash value and digitally signed with keys stored in a secure hardware enclave.

The invention relates to the technical field of control systems, and provides a supervision control system, method and equipment in an industrial weaving process and a storage medium. The method comprises the following steps: acquiring engineering data and environment data in a weaving process through an intelligent sensor, and standardizing an original spatio-temporal data matrix formed by the engineering data and the environment data to generate an engineering matrix; attribute information including elasticity, fluid and heat conduction is generated based on the engineering matrix, and a space model representing the weaving process state is constructed based on the attribute information; generating a dynamic control parameter based on the deviation between the model parameter of the spatial model and the target trajectory; generating a tension signal for the dynamic control parameter and a preset target tension, and generating an execution instruction through the tension signal to control the weaving equipment to operate. A multi-physics field coupling space model is constructed, dynamic control parameters are generated according to the deviation between model parameters and a target track, and an accurate closed-loop supervision control process from data perception to equipment control is formed.

The invention discloses a robot and an intelligent interaction method thereof, and relates to the technical field of robots, and the robot comprises an instruction obtaining module which is used for converting external instruction information into text information; the artificial intelligence module is used for performing vectorization processing and similarity comparison on the text information and keywords in a preset task list through a large model to obtain a conventional target task and an unconventional target task; the task decomposition module is used for decomposing the conventional target task or the unconventional target task into a plurality of sub-tasks and determining solutions matched with the sub-tasks according to the types of the sub-tasks; the task execution module is used for supervising and controlling execution of each subtask; the memory module is used for storing key data and a knowledge graph database in the execution process of each subtask; and the planning decision module is used for controlling the operation of the modules. According to the invention, man-machine interaction and autonomous planning and intelligent control of the robot body can be realized.

A unification method based on data acquisition interfaces of different SCADA (supervisory control and data acquisition) production monitoring systems of a sewage plant comprises the following steps: analyzing private protocols such as Modbus through protocol conversion middleware, and standardizing data streams; establishing association between the unique identifier and the data stream by using an equipment mapping mechanism to form a data mapping table; a data normalization algorithm is adopted to unify a field format, and missing values are filled through linear interpolation. And an increment adaptation module is designed to realize compatibility of new and old system interfaces, and AES-256 encryption is combined to guarantee transmission security. The transmission rate is dynamically adjusted based on the network state, and video and production data are fused. A multi-protocol environment is adapted through an adaptive protocol adjustment module, and finally data integrity is ensured by using a CRC check and retransmission mechanism. According to the scheme, a technical closed loop from protocol conversion to multi-source fusion is constructed, the problems of data island and compatibility of the SCADA system of the sewage plant are solved, and the data management efficiency and reliability are improved.

The invention discloses an electric power inspection operation robot anti-misoperation system and method based on video analysis, and relates to the technical field of electric power equipment, and the system comprises an inspection robot which is used for collecting first real-time state data of to-be-operated equipment, and executing an operation instruction issued by a user; the video acquisition module is used for acquiring second real-time state data of the equipment to be operated; the data acquisition and monitoring control module is used for acquiring third real-time state data of the equipment to be operated; and the main control module is used for judging whether equipment state data fed back by the first real-time state data, the second real-time state data and the third real-time state data are consistent or not, and controlling the inspection robot to execute a corresponding operation instruction when the equipment state data are consistent. The situation of misoperation of the inspection robot is avoided, and therefore stable operation of a power system is guaranteed.

Systems and methods for identifying a status of components of hydraulic fracturing units including a prime mover and a hydraulic fracturing pump to pump fracturing fluid into a wellhead via a manifold may include a diagnostic control assembly. The diagnostic control assembly may include sensors associated with the hydraulic fracturing units or the manifold, and a supervisory control unit to determine whether the sensors are generating signals outside a calibration range, determine whether a fluid parameter associated with an auxiliary system of the hydraulic fracturing units is indicative of a fluid-related problem, determine whether lubrication associated with the prime mover, the hydraulic fracturing pump, or a transmission of the hydraulic fracturing units has a lubrication fluid temperature greater than a maximum lubrication temperature, or determine an extent to which a heat exchanger assembly associated with the hydraulic fracturing units is cooling fluid passing through the heat exchanger assembly.

The invention discloses a closed-loop control method for a hydraulic control butterfly valve of a PCCP (prestressed concrete cylinder pipe) long-distance high-pressure water conveying pipeline, and belongs to the technical field of long-distance high-pressure water conveying pipeline control. The problems that in the prior art, due to manual scheduling or single-point PID control, a long-distance PCCP water conveying system has response lag and lacks global cooperation, the water attack risk is difficult to effectively deal with, and the optimal overall energy consumption of the system cannot be considered are solved. According to the invention, by constructing a hierarchical control architecture in which a distributed measurement and control network is coordinated with a central supervision control and data acquisition system platform, a variable-parameter PID control algorithm is built in an equipment PLC, so that millisecond-level identification and active suppression of a sudden water attack working condition are realized; a hydraulic simulation model and a multi-objective optimization algorithm are deployed in a central supervision control and data acquisition system master station, and a whole-line optimal pressure set value is solved through iterative calculation and is issued to each PLC for execution, so that the system energy consumption minimization is realized on the premise of ensuring the pipeline safety.

The invention provides a chopped chilli fermentation jar temperature remote regulation and control system and method based on supervision and control, and relates to the technical field of temperature remote regulation and control. The abnormal confidence coefficient of the temperature of the chopped chilli fermentation jar in the current chopped chilli fermentation period is determined; calibrating the temperature value of each temperature sensor; further generating temperature regulation and control instructions of a heating rate control section and a constant temperature maintaining section in the current chopped chilli fermentation period; when the abnormal confidence exceeds a set threshold value, a semiconductor temperature control module on the outer wall of the chopped hot pepper fermentation jar body is remotely controlled to execute a temperature regulation and control instruction, temperature gradient distribution in the chopped hot pepper fermentation jar is continuously monitored in the instruction execution process, and then the distribution proportion of the heating power and the refrigerating power of the semiconductor temperature control module is adjusted. According to the application, the internal temperature of the chopped chilli fermentation jar can be remotely and accurately regulated and controlled in a high-acid, high-salt and high-humidity chopped chilli fermentation environment, so that the uniform distribution of the internal temperature of the fermentation jar is improved.

The invention discloses a wind-solar hydrogen storage and charging multi-energy complementary integrated system and a cooperative control method thereof, and belongs to the technical field of supervision control and data acquisition, and the method comprises the following steps: firstly detecting the fluctuation index of the output power of a power generation side, and starting the absorption of a super capacitor and the PID adjustment buffering of a lithium battery; and evaluating the state of the electrolytic cell, and determining whether or not and how to accurately adjust the feed water flow according to the water content and humidity distribution variance. And finally responding to the load change rate. According to the wind and light hydrogen storage and charging multi-energy complementary cooperative control method provided by the invention, accurate management of all working conditions of the electrolytic cell is realized through a three-step cooperative closed-loop control logic. A complete chain of'prevention-response-optimization 'is formed from source protection of power fluctuation on a power generation side, dynamic correction of the state of the electrolytic cell and graded adjustment of load change. The core value of the method lies in that through multi-parameter linkage, the damage risk of the proton exchange membrane is reduced to the maximum extent, and efficient and stable operation of the electrolytic cell is guaranteed.

The invention discloses a large-scale wind turbine generator wind energy tracking control time history optimization method considering an aging effect. The method comprises the following steps: S100, quantitatively evaluating unit performance degradation, performing SCADA (Supervisory Control and Data Acquisition) parameter selection and data preprocessing, constructing a unit performance degradation quantitative evaluation model, and evaluating the aging state of a unit through field SCADA data; s300, optimizing the control time history of the unit, and judging the deterioration state of the unit through SCADA (Supervisory Control and Data Acquisition) data; and S200, maximum wind energy tracking control is carried out, a blade tip speed ratio-wind energy utilization coefficient curve under the aging state of the unit is drawn according to the evaluated aging state of the unit, the basic performance of the wind turbine generator is approximately described, and the maximum value of the wind energy utilization coefficient is obtained. The optimization method is provided for solving the problem that the wind power utilization coefficient of the wind turbine generator is reduced due to natural aging of the wind turbine generator, so that the power output of the wind turbine generator is directly influenced, the optimal operation condition parameters of the wind turbine generator in the aging state can be more accurately obtained, the operation condition is optimized, and the operation power generation efficiency is improved.

The invention discloses a distribution network substation voltage control method, electronic equipment and a medium, and the method comprises the steps: constructing an IBDBN-DGAM network which comprises an input layer, an IBDBN module, a DGAM module and a decision layer; wherein the IBDBN module is used for carrying out deep feature extraction and probability modeling on input data based on a multilayer Bayesian network structure, and the DGAM module is used for dynamically adjusting the weight of a network topology structure by utilizing a dynamic graph attention mechanism based on feature representation output by the IBDBN; historical multi-modal data of a distribution network substation is used as input data to be input into an IBDBN-DGAM network; an objective function is constructed to optimize the IBDBN-DGAM network; wherein the multi-modal data of the distribution network substation comprises voltage, current and load data from an SCADA (supervisory control and data acquisition) system and a PMU (power management unit); and acquiring real-time multi-modal data of the distribution network substation, inputting the real-time multi-modal data into the optimized IBDBN-DGAM network, and outputting to obtain a voltage control instruction.

The invention discloses an SCADA (supervisory control and data acquisition) system optimization method for an intelligent power grid, which improves data processing efficiency and system response speed by performing data grading processing on edge computing nodes, and reduces data transmission load by adopting a differential transmission strategy and an intelligent compression technology. A deep learning algorithm is utilized to construct a self-learning fault prediction model to enhance fault prediction and diagnosis capability, a multi-layer data security and privacy protection mechanism is introduced to improve data security and privacy protection, and an intelligent scheduling module is introduced to enhance system collaboration and dynamic adaptability. According to the comprehensive optimization methods, the real-time performance, reliability and safety of the SCADA system are remarkably improved, so that the SCADA system is more suitable for the complex environment of the smart power grid, and the efficient, stable and safe operation requirements of the smart power grid for the SCADA system are met.

The invention discloses a supervision and control-based punctual scheduling method and system for wafer combination equipment, and mainly solves the problems of high probability of blockage, path conflict and low scheduling efficiency during multi-resource parallel operation of the existing wafer combination equipment. According to the implementation scheme, the method comprises the following steps: respectively constructing corresponding automaton models for process units in equipment, and carrying out synchronous splicing according to a real process flow to form an overall model capable of reflecting dynamic behaviors of a system; a corresponding constraint model is established by combining factors such as process sequence constraint, equipment capacity limitation, carrying time constraint and residence time limitation; and the supervision controller continuously judges whether the event to be executed can cause blockage or not, gradually eliminates the blockage by disabling the controllable event, triggers the optimal event according to the priority of the event, and guides the scheduling path to propel and output the optimal scheduling scheme along the optimal direction. According to the method, the overall model capable of being dynamically adjusted is constructed, the event priority and multi-class constraint collaborative optimization scheduling is utilized, the wafer residence time can be remarkably shortened, the overall scheduling efficiency is improved, and the method can be used for operation inspection, evaluation and optimization of an equipment system.

Systems and methods are disclosed herein for predictive maintenance using computational models. The systems and methods can receive data from a supervisory control and data acquisition (SCADA) system and condition monitoring systems (CMSs), generate, using anomaly detectors, anomaly scores, and generate, using an augmented data fusion model, a health state prediction of a component of a machine. An extract, transform, and load (ETL) module can extract and transform data from a variety of sources, including SCADA systems, CMSs, and other computing devices to create model input data. A models module can analyze such model input data to determine which computational models can run on the input data. A prediction module and confidence interval data can hone the predictions created by the models module. A feedback module and the ETL module can be used on diagnostic data, configuration data, and updated SCADA and CMS data to improve the computational models.

The invention discloses a wind driven generator fault diagnosis method based on missing SCADA data and a self-adaptive time-sensitive multi-head attention mechanism, and relates to the technical field of wind driven generator fault diagnosis and prediction. In order to solve the technical defects in the prior art that errors and error accumulation are caused by data missing, only data interpolation is concerned, and time sequence dependence modeling is insufficient in the existing fan fault diagnosis work, the technical scheme provided by the invention comprises the following steps: collecting monitoring data in a wind turbine generator SCADA system to form an SCADA data matrix; carrying out numerical value standardization processing on the SCADA data; performing segmentation extraction on the time sequence data, constructing a missing indication matrix, and generating a missing value mapping matrix; extracting time sequence dependence characteristics of the SCADA data, and generating a dynamic time sequence dependence mapping matrix; and generating a fan fault prediction result according to the dynamic time sequence dependence mapping matrix. The method is suitable for intelligent operation and maintenance of a wind power plant, SCADA data analysis, equipment health management, predictive maintenance and the like.