5873 results about "Steam turbine" patented technology

The invention relates to the field of power equipment data processing, in particular to a steam turbine vibration fault diagnosis system fused with deep learning. Comprising a dynamic knowledge base construction module, a working condition adaptive data synchronization module, a knowledge-guided heterogeneous feature fusion module, a dynamic structure neural network module, an online self-optimization weight distribution module and a knowledge-enhanced coupling fault reasoning module. The dynamic knowledge base construction module updates the multi-modal knowledge graph through an incremental knowledge distillation mechanism, and generates an interpolation strategy template and a frequency band sensitivity matrix; the working condition self-adaptive data synchronization module dynamically calls an interpolation algorithm based on a rotating speed fluctuation mode to realize time sequence alignment optimization of multi-source sensor data; the system effectively solves the problems of time scale asynchronism and feature heterogeneity in multi-source heterogeneous data fusion through a knowledge-driven and data-driven closed-loop interaction mechanism, and realizes accurate diagnosis and early warning of steam turbine vibration faults under complex working conditions.

The invention relates to the technical field of thermal power plant parameter regulation and control, in particular to an intelligent temperature and pressure regulation method and system for a thermal power plant, and the method comprises the following steps: collecting temperature, pressure and flow data based on heat transfer and flow channels among a boiler, a steam turbine, a condenser and heat exchanger equipment in the thermal power plant; constructing a network structure representing interaction between devices, evaluating heat exchange characteristics of nodes, and constructing heat flow path structure matrix information; according to the method, the complex interaction among the boiler, the steam turbine, the condenser and the heat exchanger equipment is accurately quantified by constructing the heat flow path network structure among the equipment and evaluating the heat exchange characteristics of the nodes. Thermal inertia feedback matrix information is introduced, and transient changes of temperature and pressure are monitored in real time, so that delay and inertia effects in heat transfer and fluid flowing between equipment can be more accurately captured, and the response speed and precision to different loads and working conditions are improved.

The invention provides a valve actuator dispatching control method and system based on AI intelligence, and relates to the technical field of industrial automation control, and the method comprises the steps: collecting the running state parameters of a steam turbine in real time, determining the relation between the steam inlet amount and the valve opening degree under the current working condition to obtain a preliminary valve opening degree estimated value, and carrying out dynamic response compensation; the method comprises the following steps: carrying out comprehensive coupling analysis on a theoretical valve opening value and mechanical parameters such as response time, inertial parameters and an opening limit threshold value of a valve actuator, calculating a dynamic adjustment weight and carrying out boundary constraint processing to obtain a processed parameter, and calling a preset valve opening-silicon controlled trigger angle nonlinear mapping model in a single chip microcomputer based on the parameter; and calculating a final silicon controlled trigger angle by inquiring adjacent data points and a linear interpolation method. By fusing intelligent prediction, multi-dimensional adjustment and a closed-loop feedback mechanism, the valve control precision and response speed are improved, and efficient and intelligent operation of industrial automatic control is achieved.

The invention relates to the technical field of steam turbine testing, in particular to a testing system for mismatch correction of a wide-load-interval thermal power generating unit speed regulation model, which comprises a thermodynamic system component, a speed regulation system device, a dynamic signal acquisition device and a control device, a dynamic signal processing module analyzes the relevance between main steam pressure sudden change and control valve opening oscillation in real time, a dynamic response database including a time sequence is constructed, and a control valve opening feed-forward compensation instruction and a combustor fuel distribution gradient adjustment signal are generated according to correction parameters. Power over-modulation wave crests caused by sudden load change are suppressed, and primary frequency modulation action delay is reduced; and the simulation verification module compares measured data with model output through an error feedback mechanism, dynamically adjusts high-pressure cylinder flow characteristic curve calibration parameters, optimizes a control strategy in combination with a network-related safety margin evaluation result, and realizes improvement of dynamic response precision in a full peak regulation interval and enhancement of power grid frequency stability.

The invention discloses a carbon capture and energy storage and thermal power generation coupled energy comprehensive utilization system, which comprises a thermal power generation system, an energy storage system and a carbon capture system, and is characterized in that a compression energy storage unit of the energy storage system is coupled to a feed water heat regeneration unit of the thermal power generation system; an expansion energy release unit of the energy storage system is coupled to a steam turbine generator set of the thermal power generation system, and a steam-water cycle working medium in the thermal power generation system serves as a heat storage and cold storage medium of the carbon dioxide energy storage system. The carbon capture system is coupled between the thermal power generation system and the carbon dioxide energy storage system, captures carbon dioxide gas in the flue gas, inputs the carbon dioxide gas into the carbon dioxide energy storage system to serve as a circulating working medium, and heats the circulating working medium in the expansion energy release unit through waste heat of the flue gas. According to the scheme, the operation efficiency of the thermal power generation system and the operation efficiency of the carbon dioxide energy storage system can be improved, the overall energy utilization efficiency of the system can be improved, and meanwhile the emission amount of gas pollutants is reduced.

The invention discloses an intelligent operation and maintenance system, method and equipment for steam turbine lubricating oil and a storage medium, and relates to the technical field of industrial digital intelligent operation and maintenance. Zero loss and low delay of data are guaranteed through the data transmission module, and the data fault problem of traditional manual meter reading is solved; static parameters are converted into dynamic trend, residual life and abnormal early warning through a hybrid model of a visual cloud operation and maintenance module, and intelligent conversion from data to decision is realized; and the oil filtering execution module automatically responds to the instruction to complete closed-loop treatment from polluted oil liquid to clean oil liquid without manual intervention, so that real-time monitoring and intelligent analysis of the running state of the steam turbine are realized, an oil filtering system is automatically started when a set threshold value is reached, the oil liquid is ensured to be in a normal state, the maintenance cost is reduced, and the operation and maintenance efficiency is improved.

The invention provides a thermoelectric unit intelligent early warning method and system based on an artificial intelligence model. The method comprises the steps that firstly, multi-source operation monitoring information of different operation dimensions of core components such as a turbine, a boiler and a generator of a thermoelectric unit is obtained; performing time sequence correlation analysis on each modal monitoring data, constructing a dynamic correlation matrix, generating a modal conflict correction coefficient, and obtaining a time sequence dependence feature set; inputting the model into a hierarchical evolutionary early warning model, and obtaining an evolutionary fusion early warning feature vector through modal conflict correction and dynamic feature evolution modeling; generating a working condition self-adaptive dynamic early warning threshold value based on the current operation working condition; through comparison and abnormal traceability of the traceability verification module, an abnormal root component and a propagation path are determined, and a targeted traceability early warning instruction is output, so that the early warning accuracy and adaptability of the thermoelectric unit are improved, and safe and stable operation of the unit is guaranteed.

The invention discloses a steam and fused salt coupled heat storage and release peak shaving system and method. The existing steam sensible heat molten salt heating or pure electric molten salt heating technology has the problems of complex technical process, high construction cost, high implementation difficulty, low system electricity-electricity conversion efficiency and the like. The system comprises a fused salt storage system, a heat storage and exchange system, a heat release and exchange system, boiler equipment and steam turbine equipment, an outlet of the boiler equipment is connected with the steam turbine equipment and the heat storage and exchange system, the fused salt storage system is connected with the heat storage and exchange system and the heat release and exchange system, and the heat release and exchange system is connected with the steam turbine equipment. According to the invention, machine-boiler decoupling and electric heat storage peak regulation of a traditional thermal power plant can be realized. In the heat storage process, latent heat and sensible heat energy of main steam are stored in a fused salt storage system through a heat storage and exchange system, and deep peak regulation and energy storage are achieved; and in the heat release process, heat in the fused salt storage system is released through the heat release heat exchange system, and steam is prepared and supplemented into steam turbine equipment so as to improve the power generation power.

The invention provides a power plant deep peak regulation and power generation optimization method and system based on steam extraction energy storage, and relates to the technical field of power grids, the method comprises the steps that high-temperature and high-pressure steam is generated through a steam turbine, the steam enters a steam extraction system, and the steam extraction system is used for extracting part of steam exhausted by the steam turbine when the load of the power grid is low; the extracted steam is conveyed into the energy storage device to be stored; based on historical power grid load data and real-time load prediction data, dynamic optimization adjustment of generated power is carried out by combining characteristics of a generator set of a power plant, and deep peak regulation operation of the generator set in a low-load operation state is realized by controlling a power generation dispatching control module of the power plant. The output power of each unit is adjusted through an optimization algorithm; when the load of the power grid is low, part of steam of the steam turbine is stored in the energy storage device through the steam extraction system, and when the load of the power grid is peak, the stored steam flows back to the steam turbine again to be reused.

The invention relates to the technical field of control and adjustment, in particular to a steam turbine fault diagnosis system based on multi-parameter fusion monitoring, which is characterized in that a quantum hybrid sensing module is used for establishing a picosecond-level space-time reference through entangled photon pair distribution, and unifying a time sequence label of multi-source heterogeneous data; the hypergraph feature extraction module loads the coefficient to a vibration measurement point vertex attribute channel, dynamically calculates a heat conduction hyperedge weight according to a rotor eccentricity inversion value, aggregates temperature field, vibration spectrum and magnetic domain features in a space-time hypergraph which retains physical topology, outputs a cross-scale aligned fusion feature tensor, and outputs a vibration measurement point vertex attribute channel; generating a diagnosis feature vector to drive a multi-scale twin experience certificate; and the federation decision module triggers a load reduction instruction according to the microscopic crack cloud picture to inhibit thermal stress sudden change, and meanwhile, the feature representation precision is improved through cloud federation optimization hyperedge weight parameters. According to the method, the problem of characterization distortion caused by time sequence asynchronization and scale mismatch of heat and machine coupling data is solved.

A turbine engine for an aircraft including a combustor, a turbine, and a steam system. The combustor generates combustion gases. The turbine receives the combustion gases and is drivingly coupled to a shaft. The steam system includes a boiler, a superheater, and a steam turbine. The boiler receives water and is fluidly connected to the combustor to receive a first portion of the combustion gases from the combustor and to boil the water to generate steam. The superheater is located downstream of the combustor to receive a second portion of the combustion gases from the combustor and to heat the steam. The steam turbine is fluidly coupled to the superheater to receive the steam from the superheater and to rotate the steam turbine. The steam turbine is drivingly coupled to the shaft.

A turbine engine for an aircraft. The turbine engine includes a combustor, a turbine, a boiler, a steam turbine, and a reheat boiler. The combustor generates combustion gases and the turbine is positioned downstream of the combustor to receive the combustion gases and to rotate the turbine. The boiler is positioned downstream of the combustor to receive the combustion gases and to boil water to generate steam. The steam turbine is fluidly coupled to the boiler to receive the steam from the boiler and to rotate the steam turbine. Each of the turbine and the steam turbine is drivingly coupled to a core shaft to rotate the core shaft. The reheat boiler is fluidly coupled to the steam turbine to receive the steam from the steam turbine and to reheat the steam. The combustor is fluidly coupled to the reheat boiler to receive the reheated steam.

The invention discloses an intelligent thermal power plant hierarchical optimization control method based on multiple agents, and the method comprises the steps: obtaining the observation data of each thermal power generating unit agent, each wind and light storage agent and each deduction agent through an upper-layer plant-level scheduling decision agent, and calling a preset multi-agent reinforcement learning module, modeling the electric heating load optimal distribution problem of the thermal power plant, and solving to obtain an optimal load distribution result of each thermal power generating unit intelligent body and each wind and light storage intelligent body; the lower-layer equipment level control agent defines a steam turbine, a boiler body, boiler auxiliary equipment and a heat supply steam extraction device in each thermal power generating unit as corresponding equipment agents according to the optimal load distribution result of each thermal power generating unit agent, and integrates interaction information, equipment operation data and equipment parameter control mechanisms among the equipment agents; and carrying out equipment-level multi-agent optimization control modeling by taking a load distribution result and the minimum operation cost as targets, and solving to obtain an optimal control instruction of each equipment agent.

The invention relates to the technical field of peak regulation of power generation systems, in particular to a multi-mode power generation system for a new energy large base and an operation method of the multi-mode power generation system. The multi-mode power generation system comprises a thermal power station and a fused salt energy storage power station. The thermal power station comprises a boiler, a first turbine, a first water return unit and a first generator; the fused salt energy storage power station comprises a high-temperature fused salt tank, a low-temperature fused salt tank, a fused salt heating unit, a steam-water heating unit, a second water return unit, a second steam turbine and a second generator; an air inlet of the fused salt heating unit is configured to obtain steam flowing out of the boiler, and a second discharging opening of the fused salt heating unit is connected with the first water return unit; an air outlet of the steam-water heating unit is connected with the first steam turbine and the second steam turbine. The first water return unit and the second water return unit are connected with a second feeding port of the steam-water heating unit. The multi-mode power generation system can set different operation modes according to different requirements, so that the new energy large base can meet higher requirements.

The invention relates to the technical field of multi-energy complementary power generation, and discloses an industrial steam supply peak shaving system and method coupling fused salt heat storage and solar energy, and the industrial steam supply peak shaving system comprises a coal-fired power generation system and an industrial steam supply system; in the heat storage mode, the boiler, the steam cooler and the condenser are sequentially connected; in the heat release mode, the high-pressure heater, the primary feed water heater and the low-pressure cylinder are sequentially connected through pipelines; and the feed pump, the secondary feed water heater and the boiler are connected in sequence. In the low ebb of the electrical load, solar energy is used for heating fused salt to store heat, and part of high-temperature steam is extracted from steam-water circulation of the improved coal-fired power generation system to store the heat in a heat storage device and does not enter a steam turbine for power generation; the power load output is adjusted by adjusting the thermal load output of the thermodynamic system in the power generation process, and load decoupling of the boiler and the steam turbine is achieved. And in the electrical load peak, the stored heat energy is released back to steam-water circulation, and the electrical load of the coal-fired power generation system is increased.

The invention discloses an energy storage-heat pump linkage heat, power and cold collaborative peak regulation system and an operation method. The system comprises a combined heat and power generation unit, an evaporator, a condenser, a compressor, wind power and photovoltaic power generation equipment, an electric power controller, a cross-seasonal energy storage chamber and the like. Surplus electric quantity of a power grid is consumed through a heat pump and converted into heat energy and cold energy in a power off-peak period, and part of condensed water of a steam turbine is heated through heat storage in a power peak period to improve the power output of a unit; the unit heats heating return water through heat storage release and steam turbine steam extraction in a cascade mode in winter, electric heating peak regulation is achieved, external cooling and electric cooling peak regulation are achieved through electric cooling conversion and cold energy release in summer, and cross-seasonal energy storage and peak regulation are achieved through electric heating and cold conversion in spring and autumn. Power storage is replaced by cold storage and heat storage, peak regulation is promoted through heat supply and cold supply, and the new energy power consumption level can be greatly improved.

The invention discloses a steam turbine safe operation health assessment method and system, and belongs to the technical field of steam turbine monitoring. The method comprises the following steps: acquiring running data of a steam turbine in real time through a multi-source sensor network deployed on key components of the steam turbine; the method comprises the following steps: preprocessing original operation data of a steam turbine by adopting edge computing equipment to generate a time domain waveform analysis diagram or a time sequence analysis diagram; transmitting the preprocessed structured feature data to an operation and maintenance management platform, inputting a fault diagnosis model for analysis, pre-training through a historical fault case library, and aligning feature distribution of the historical case library and current equipment data through a domain adaptive algorithm in transfer learning; and inputting a diagnosis result into a self-adaptive dynamic evaluation model based on a reinforcement learning engine, dynamically adjusting a model weight and an alarm threshold according to real-time working condition parameters, outputting a health score and a maintenance decision, and forming a closed-loop process of perception-edge processing-cloud diagnosis-dynamic optimization-decision output.

The invention relates to the technical field of equipment fault diagnosis, and discloses a steam turbine vibration fault risk evaluation method and system.The method comprises the following steps that real-time data such as vibration, temperature, pressure and rotating speed of a steam turbine are collected through multiple sensors; the sensors comprise an accelerometer, a displacement sensor, a temperature sensor, a pressure sensor and a rotating speed sensor; the collected multi-source data is preprocessed, including de-noising, time synchronization and data standardization, to eliminate environmental noise and time difference between the data. The technical scheme based on multi-dimensional data acquisition and fusion is adopted, vibration sensors, temperature sensors, pressure sensors, rotating speed sensors and the like are arranged at key parts of a steam turbine, the running state of equipment is obtained in real time, multi-dimensional fusion and feature extraction are carried out on data, and the effects of comprehensive and real-time monitoring and early prediction of vibration faults of the steam turbine are achieved.

The invention provides a steam turbine, a regenerative system and a control method thereof, and the method comprises the steps: collecting data through a multi-mode sensor such as a steam pressure sensor, and constructing a digital twin model containing a thermodynamic equation and equipment aging parameters through the fusion of a space-time alignment algorithm; model deviation is predicted and dynamically calibrated by means of an LSTM network, a near-end strategy optimization algorithm is adopted to solve a Pareto optimal solution of heat recovery efficiency maximization and corrosion rate minimization in a digital twin environment, and a control instruction is generated. And when the corrosion prediction risk exceeds a threshold value, a control strategy is dynamically adjusted, and health-efficiency cooperative control is realized. Meanwhile, the invention further relates to a corresponding collaborative optimization device and corrosion monitoring equipment, and a multi-modal data fusion module is deployed at an edge computing node to realize efficient data processing and analysis. The thermodynamic cycle efficiency of the steam turbine regenerative system is effectively improved, the corrosion risk is reduced, the service life of equipment is prolonged, and remarkable economic and technical benefits are achieved.

The invention discloses a steam turbine regulating valve state evaluation method, and belongs to the technical field of thermal power plant steam turbine valve state monitoring, and the method comprises the steps: collecting the video stream data and operation data of a to-be-evaluated steam turbine regulating valve rod, recognizing the contour of the valve rod based on a YOLOv5 model according to the video stream data, and outputting the feature points of the valve rod; tracking the two-dimensional coordinates of the feature points of the valve rod to calculate the vibration parameters of the valve rod; the method comprises the following steps: calculating a Pearson correlation coefficient of operation data, screening vibration parameters related to a jam fault to generate a time domain displacement sequence, performing time alignment with the operation data, performing fast Fourier transform to obtain a frequency spectrum, and identifying a dominant frequency component, a frequency multiplication component and a sideband frequency; calculating a frequency deviation and an energy distribution difference based on a preset reference spectrum library; and judging the jam grade according to the frequency deviation and the energy distribution difference. The technical problem that the jamming fault level cannot be accurately quantified by an existing turbine regulating valve state monitoring method is solved.

The invention provides a steam turbine set vibration fault diagnosis method and system, and belongs to the technical field of thermal power plant fault diagnosis. The method comprises the following steps: inputting a to-be-identified vibration signal of a turboset into a trained turboset vibration fault diagnosis model for vibration fault diagnosis; the training rule of the steam turbine set vibration fault diagnosis model comprises the following steps: extracting a discrete wavelet transform coefficient from a steam turbine set vibration signal to obtain a DWTC image, and converting the steam turbine set vibration signal into a vibration signal image; taking the DWTC image and the vibration signal image as inputs of two branches of a double-flow convolutional neural network to perform high-level feature learning, and fusing high-level feature images output by the two branches of the double-flow convolutional neural network after preset processing; and inputting the fused image features obtained by fusion into a preset classifier, and outputting a corresponding turboset vibration fault type. The method and the system have the advantages of high accuracy, good generalization ability and strong robustness.

The invention relates to the field of industrial equipment monitoring, and discloses a power plant steam-water system edge calculation monitoring terminal system, which comprises a data acquisition module used for performing real-time acquisition on temperature, pressure, flow and liquid level parameters of key parts such as a boiler, a steam turbine and a pipeline in a power plant steam-water system, an acquisition result is converted into a standard data format to be output; the edge calculation module is used for performing local processing on the data, including feature extraction, data modeling, anomaly recognition and operation state analysis, and the module establishes a state model based on historical data and outputs parameter optimization suggestions according to a set strategy; and the communication module is used for transmitting the processing result to a monitoring center and receiving an instruction issued by the monitoring center. Local modeling and recognition are carried out on collected data through the edge calculation module, delay caused by data return is avoided, an abnormal early warning mechanism of second-level response is achieved, and the fault handling capacity of the system is enhanced.

The utility model provides a thermal power and compressed air energy storage coupled deep peak regulation coaxial unit which comprises a thermal power station boiler and further comprises a power generator, a steam turbine unit, a compressor unit, a motor / power generator and an expansion unit which are coaxially connected in sequence. The gas output end of the compressor unit is connected with the input end of the gas storage tank, and the output end of the gas storage tank is connected with the gas input end of the expansion unit; the steam turbine unit comprises a high-pressure cylinder, an intermediate-pressure cylinder and a low-pressure cylinder which are coaxially connected in sequence; a superheated steam pipeline of a thermal power station boiler is communicated with the gas input end of a high-pressure cylinder, the gas output end of a low-pressure cylinder is connected with the shell pass input end of a condenser, and the shell pass output end of the condenser is connected with the tube pass of a low-pressure heater through a condensate pump. The tube pass of the low-pressure heater is sequentially connected with the tube pass of the deaerator and the tube pass of the high-pressure heater, and the tube pass of the high-pressure heater is connected with the thermal power station boiler to form a loop. The advantages of the compressed air energy storage technology are fully exerted, peak regulation can be achieved on the premise that the operation efficiency of the thermal power generating unit is not reduced, meanwhile, the rapid regulation characteristic and flexibility of the unit are improved, and the capacity of the unit for responding to the peak regulation requirement of a power grid is greatly improved.

The invention discloses a thermal power generating unit, flywheel and compressed air hybrid energy storage system and an operation method, and relates to the technical field of flexibility improvement of novel energy storage and thermal power systems. The system comprises a flywheel energy storage subsystem, a compressed air energy storage subsystem, a thermal power collaborative heat exchange system, a flywheel-CAES switching coupling module and an intelligent control system. The flywheel energy storage subsystem is responsible for millisecond-level frequency modulation response, the compressed air energy storage subsystem provides minute-level stable output, and the flywheel energy storage subsystem and the compressed air energy storage subsystem cooperatively work through an intelligent control system to realize a composite regulation mode of'fast response-high capacity '; a compressed air side is coupled with a thermal power plant turbine steam extraction system, a boiler flue gas system and a condensed water system to improve the energy release efficiency; the flywheel side interacts with a power grid in real time through a bidirectional converter, and rapid frequency support is achieved. The system has the quick response capability and the long-time energy supporting capability, the frequency modulation and peak regulation performance of the thermal power generating unit is remarkably improved, and the system has high engineering popularization value and application prospects.

The invention belongs to the technical field of energy storage, and relates to a compressed air and water coupled multi-energy co-production energy storage system and method, comprising an air compressor, a first heat exchanger, a second heat exchanger, an air turbine and a cooling module; a circulating medium of the first circulating loop is fused salt; the circulating medium of the second circulating loop is water, and the second circulating loop comprises a low-temperature water tank, a first booster pump, a second heat exchanger, a high-temperature water tank, a flash tank, a third heat exchanger, a steam turbine high-pressure cylinder and a heating module which are sequentially communicated end to end. Compression heat generated by compressed air can be stored in fused salt and water, special geographical conditions needed for storing high-pressure air are avoided, meanwhile, in the energy release stage, the stored water is used for flash evaporation and fused salt heating and then enters a steam Rankine cycle to do work, combined heat and power generation can be achieved in winter, combined cooling and power generation can be achieved in summer, and the energy-saving effect is achieved. Therefore, combined supply of different kinds of energy in different seasons is achieved, and the energy supply efficiency is improved.

The invention relates to the technical field of intelligent operation and maintenance of ship power equipment, in particular to a DLinear-Transform-based anomaly detection method for a marine power generation steam turbine system, and the method comprises the steps: S1, carrying out the collection and processing of non-stationary time series data of the marine power generation steam turbine system; s2, constructing a DLinear-Transform model framework, and carrying out the construction of the DLinear-Transform model framework; s3, carrying out anomaly detection on the marine power generation steam turbine system on the basis of DLinear-Transform; and S4, verifying the performance of the model public data set. According to the method, a DLinear-Transform fusion framework is constructed, and anomaly detection of the key parameters of the ship power generation steam turbine system under the non-stable working condition is realized based on the DLinear linear characteristic and the Transform context modeling capability. Through SMD, SWaT and actual marine power generation steam turbine data set verification, the method is superior to existing optimal models such as TransAD and the like. Compared with an existing ship intelligent operation and maintenance technology, the system equipment anomaly detection and fault prediction capability is improved, and a new technical architecture is provided for predictive maintenance of ship power equipment.

The invention relates to the technical field of electric power automation control, and discloses a coordinated control system for a generator set, which adopts an intelligent DCS integrated design architecture and performs real-time data interaction with a set decentralized control system through hard wiring or a communication protocol. According to the system, through deep fusion of a model prediction control algorithm and intelligent DCS integrated design, a boiler-steam turbine dynamic coordination model is constructed, and a control instruction is generated in real time in combination with a rolling optimization strategy. By means of the design, the main steam pressure deviation is controlled within + / -0.2 MPa, and the load response rate reaches 1.5% Pe / s and is improved by more than 40% compared with a traditional system. Particularly, under the working condition of deep peak regulation, by means of decoupling control over a fuel-air supply-water supply loop through a neural network algorithm, main steam temperature fluctuation (within + / -5 DEG C) and reheater spray desuperheating water quantity sudden change (the change rate is smaller than or equal to 10 t / min) are effectively restrained, the control quality of a unit under the conditions of variable loads and variable coal quality is remarkably improved, and the control efficiency of the unit is improved. And the high-standard requirement of the power grid on the AGC performance is met.

The invention belongs to the technical field of fused salt energy storage, and particularly relates to a start-stop peak regulation coal-fired power generation system and method coupled with fused salt energy storage. According to the system and method for achieving safe and efficient start-stop peak regulation of the unit through coupled fused salt energy storage, when the unit needs to be shut down, a boiler operates at the lowest stable combustion load, a back pressure turbine is arranged to absorb boiler main steam to provide necessary auxiliary power for the unit, and fused salt and a water heat storage system are added to store boiler hot resteam; the original steam turbine of the unit stops, and the unit stops and does not stop the boiler; heat stored by the fused salt and water heat storage system is used for generating steam in unit starting and load increasing stages to increase the load increasing rate of a unit turbine. According to the method, the operation safety problem, the economical problem and the service life loss problem of unit start-stop peak regulation are solved.

The invention discloses a turbine spindle bearing fault diagnosis method, and belongs to the technical field of turbine fault diagnosis. The method solves the problems that the fault diagnosis accuracy of an existing method is low, and an existing model is difficult to deploy and apply in an actual industrial scene due to a complex structure. According to the noise adaptive random convolution block, the model is guided to form inductive bias for global information through random disturbance on local features of vibration signals, the sensitivity to noise is remarkably reduced while key features of a fault are reserved, and meanwhile, the complexity of the model is simplified. The global attention mechanism can effectively enhance the attention capability of the model on key fault features, and has good noise identification capability. Meanwhile, the model has good nonlinear dynamic characteristic modeling capability, high-precision turbine main shaft bearing fault identification can still be realized in a high-noise environment, and the number of model parameters is small. The method can be applied to turbine fault diagnosis.

The invention discloses a steam turbine fault diagnosis method and system based on a knowledge graph, and the method comprises the following steps: S1, synchronously collecting the vibration signal, the iron abrasive particle concentration, the oil viscosity and working condition parameters of a steam turbine bearing in a steam turbine, and relates to the technical field of steam turbine fault diagnosis. In order to solve the problems that a turbine bearing serving as a core rotating part is prone to abrasion faults, and early abrasion such as surface microcracks and oil film degradation concealment is high, vibration signals, iron abrasive particle concentration, oil viscosity and working condition parameters are synchronously collected to generate multi-source data streams with aligned timestamps, nonlinear feature extraction is combined, and a multi-source data stream with aligned timestamps is obtained. By constructing the initial knowledge graph, mapping the extracted features to the initial knowledge graph and generating the dynamic knowledge graph based on the graph neural network, time sequence reasoning of the bearing abrasion state is achieved, so that the early abrasion features of the turbine bearing can be obtained, and early warning is conducted according to the early abrasion features of the turbine bearing.