4203 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 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 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 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.

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 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 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 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 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 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.

The invention belongs to the technical field of parameter identification, and provides a thermal power generating unit electro-hydraulic servo system PID parameter identification method and system, and the method comprises the steps: obtaining the historical operation data of a steam turbine, carrying out the preliminary screening of the data, and constructing a parameter identification data set; according to the mean square error between the actual value and the calculated value of the opening degree of the valve, an objective function of PID parameter identification of the DEH electro-hydraulic servo system is established; setting population initial parameters, and generating a chaotic initial population; based on a parameter identification data set and a target function, introducing an initial population value of the generated chaotic initial population into an improved Bayesian optimization model, and obtaining a preliminary optimization result through Gaussian modeling and kernel function prediction; and taking the preliminary optimization result as input, and utilizing a whale optimization algorithm introducing a Levy flight disturbance mechanism to carry out iterative search for multiple times to obtain a final optimization result. According to the invention, the parameter identification precision and robustness are improved.

The invention discloses a steam turbine maintenance decision optimization system and method based on fault cases, and belongs to the field of steam turbine fault maintenance, and the system comprises a data collection and processing module, a dynamic graph construction module, a multi-source data alignment module, a cross-domain fault simulation module, a fault causal deduction module, a maintenance strategy generation module, and a strategy adaptation migration module. According to the method, effective integration of cross-modal information can be realized, the expression ability of fault diagnosis and maintenance knowledge is enhanced, the adaptability and accuracy of the system are improved, the physical authenticity and reliability of fault prediction are improved, maintenance personnel are helped to understand a fault propagation mechanism and a risk source, and the transparency and reliability of decision making are improved; the limitation of a single scheme is avoided, it is guaranteed that a maintenance decision can respond to environment changes in time, the adaptability and efficiency of maintenance execution are improved, the maintenance effect can be rehearsed in advance, the field trial and error risk is reduced, scientific assessment and quantitative management of the risk are achieved, and the safety guarantee of the maintenance scheme is improved.

The invention provides a dynamic optimization method and system for steam turbine valve flow characteristics and a medium, and relates to the technical field of steam turbine valve flow control. The method comprises the steps that a historical curve of valve flow is acquired based on a target steam turbine cabinet; calculating an actual curve of the actual flow through a characteristic flow area identifier, and comparing the actual curve with a historical curve for judgment to obtain a curve deviation; the curve deviation is optimized according to the dual modes, and valve management parameters are obtained; and dynamically correcting the valve flow characteristics based on the valve management parameters. The technical problems that in the prior art, due to the fact that valve flow characteristic optimization depends on an off-line test and lacks the dynamic adjustment capacity, the unit operation condition adaptability is poor, the control precision is insufficient, and the frequency modulation performance and economic operation of the unit are further affected can be solved. The technical target of online real-time dynamic optimization of the valve flow characteristics of the steam turbine is achieved, and the technical effect of improving the frequency modulation response speed and the operation stability of a unit is achieved.

The invention discloses a Carnot cell system based on reversible cascade organic Rankine cycle and two-stage heat release. Comprising a bottom organic Rankine heat pump circulation loop, a top organic Rankine heat pump circulation loop, a top organic Rankine power generation circulation loop, a bottom organic Rankine power generation circulation loop, a heat storage water heat charging loop, a heat storage water first-stage heat release loop and a heat storage water second-stage heat release loop. The cascade organic Rankine cycle adopts a dry organic working medium, so that the problems of high vacuum compression, high compression ratio and high superheat degree of a compressor and wet expansion, liquid impact, corrosion and the like of a last-stage blade of a steam turbine can be effectively avoided; and through the efficient integrated structural design of a large-temperature-drop two-stage heat release system of the cascade organic Rankine cycle and the heat storage water, high-degree integration of the organic working medium Rankine heat pump cycle and the organic working medium Rankine power generation cycle loop is achieved, and meanwhile the energy storage efficiency and the round-trip efficiency of the system are improved.

The invention relates to a turbine tilting pad sliding bearing lubricating oil device and an oil temperature adjusting method. The lubricating oil device comprises an oil inlet pipe and an oil supply pipe. A mounting part is arranged at the oil outlet end of the oil inlet pipe and is provided with a rotating hole; the oil supply pipe is rotationally arranged on the rotating hole, and an oil spraying hole is formed in the outer side wall of the oil supply pipe; a rotating shifting block is arranged on the outer side wall of the oil supply pipe, a mounting groove is formed in the inner side wall of the rotating hole, an arc-shaped groove coaxial with the rotating hole is formed in the mounting groove, and the sliding end of the rotating shifting block is slidably arranged on the arc-shaped groove and divides the mounting groove into a supporting groove and a driving groove in the circumferential direction of the rotating hole; one end of the elastic piece is connected to the groove wall, away from the rotating shifting block, of the driving groove, and the other end of the elastic piece abuts against the rotating shifting block. The driving groove is filled with a driving body, and the driving body abuts against the rotating shifting block. The system can automatically adjust the temperature of the lubricating oil, has the characteristics of rapidness and high reliability, and can meet the requirement of rapid load change of a coal power unit under a novel power system.

The invention provides a backpressure adjusting method and device for a natural ventilation direct air cooling system, and the method comprises the steps: obtaining the current backpressure of a steam turbine, and executing an up-cut step sequence when the current backpressure is greater than a set backpressure first preset difference value, and the up-cut step sequence comprises the steps: setting a first target sector as a new commissioning sector, and setting a second target sector as a second commissioning sector; the control mode of the shutter opening degree of the new commissioning sector is set to be automatic adjustment within the first preset opening degree range; when the current back pressure is smaller than a second preset difference value of the set back pressure, a down-cut step sequence is executed, and the down-cut step sequence comprises the step that the control mode of the shutter of the second target sector is automatically adjusted in the first preset opening degree range from the second preset opening degree range to the second preset opening degree range till the second target sector quits operation. By controlling the automatic switching of the sectors and the automatic adjustment of the opening degree of the shutter, the automatic adjustment of the back pressure is realized, the automation degree of the back pressure adjustment is improved, the precision and efficiency of the back pressure adjustment are further improved, and the efficiency of the generator set is improved.

The invention relates to the technical field of thermal power generation, in particular to a coal-fired power plant based on fused salt heat storage, a power generation system and an operation method. The coal-fired power plant comprises a boiler, a steam turbine, a condenser, a deaerator, a first heating unit, a second heating unit and a generator. The coal-fired power plant is further provided with a first pipeline, a second pipeline, a third pipeline and a fourth pipeline, one end of the first pipeline is connected to the pipeline between the boiler and the steam turbine, and the other end of the first pipeline is connected with an air inlet of the fused salt heating unit. One end of the second pipeline is connected with an air outlet of the fused salt heating unit, and the other end is connected with the condenser; one end of the third pipeline is connected with the deaerator, and the other end is connected with an air inlet of the steam generation unit; one end of the fourth pipeline is connected with an air outlet of the steam generation unit, and the other end is connected with the turbine and the first heating unit. And the peak regulation depth and the variable load rate of the coal-fired power plant are improved.

A hybrid power generation system in one embodiment comprises a green boiler containing a thermal mass composition operable to store thermal energy, a solar energy collection system which absorbs solar energy to heat a first working fluid and in turn the thermal mass composition, and a power generation system comprising a steam turbine coupled to an electric generator to produce electricity and a nuclear steam supply system which convert a second working fluid comprising water from liquid to steam. Steam output by the nuclear steam supply system flows through the green boiler and is heated by absorbing heat from the thermal mass composition to increase the enthalpy of the steam and concomitantly electric power output from the turbine-generator. The nuclear steam supply system and green boiler may be retrofit to replace existing fossil fuel steam generation systems while retaining the energy conversion part of the fossil power plant.

The invention discloses a multivariable collaborative thermal power generating unit rapid variable load control system comprising an acquisition module used for acquiring and receiving an AGC instruction; the variable load instruction preprocessing module is used for calculating a load change rate according to the AGC instruction, and calling a dynamic model according to the load change rate to predict an energy gap in the future 30 seconds; the dynamic load feed-forward compensation module is used for generating a feed-forward control quantity through an energy gap and distributing a feed-forward instruction to the fuel quantity, the water supply quantity and the steam turbine control valve of the thermal power generating unit; the multivariable coordination control module is used for establishing a steam side-combustion side decoupling control matrix, substituting the unit state quantity acquired in real time into the steam side-combustion side decoupling control matrix, calculating to obtain a feedback correction quantity, and synthesizing to obtain a total control quantity; the parameter self-optimization engine module adopts a double-layer optimization algorithm to respectively trigger a genetic algorithm to reset parameters and an application model to predict, control and optimize local parameters in a rolling manner; and the safety constraint decision module is used for monitoring the key parameter out-of-limit risk in real time and starting load rate limitation when the key parameter out-of-limit risk is out-of-limit.

A system for measuring generator shaft voltage and shaft current, which system relates to the technical field of power systems. The system comprises a mounting component (100), which is used for mounting grounding carbon brushes (200) on a rotating shaft of a generator at the end that is close to an exciter and at the end that is close to a steam turbine, wherein the grounding carbon brushes (200) include a first grounding carbon brush (201) and a second grounding carbon brush (202) which are located at the steam turbine end of the generator, and a third grounding carbon brush (203) at the exciter end thereof; and by means of monitoring shaft voltage and shaft current in real time, a processing module (303) calculates key parameters and performs real-time analysis and spectrum analysis. When a monitored value exceeds a threshold value, the system immediately issues an alarm, thereby effectively realizing the real-time determination of the operating state of a generator and fault early warning. Moreover, the system has the functions of storing and querying historical data, by means of which operators can evaluate the insulation performance of a generator shaft and predict potential problems, and thus prevent insulation accidents caused by an overly high shaft current, thereby prolonging the service life of devices, and ensuring the continuity and stability of a power production process.

The invention relates to the field of steam turbine monitoring, and provides a steam turbine through-flow state real-time monitoring and diagnosis system based on multi-parameter fusion, and the system comprises a data fusion module which is used for collecting the operation parameters of a steam turbine in real time in a distributed manner, carrying out the fusion preprocessing of the operation parameters based on edge calculation, and outputting a data fusion set; the dynamic diagnosis module is used for pre-constructing and training a hybrid diagnosis model combined with a Bayesian network and cascade failure, identifying abnormal features in a data fusion set based on the model, comprehensively analyzing through-flow monitoring nodes based on the abnormal features by utilizing a dynamic decision tree, identifying abnormal through-flow nodes in combination with an attention mechanism and a cascade failure method, and analyzing the abnormal through-flow monitoring nodes. Generating a fault classification diagnosis result; and the distributed monitoring module is used for visually presenting a steam turbine circulation virtual model based on the fault classification diagnosis result and the through-flow monitoring node. The running state of the steam turbine can be comprehensively reflected, and the through-flow state of the steam turbine can be more accurately diagnosed.

The invention discloses an intelligent deep peak regulation system for a coal-fired power generation unit, and particularly relates to the technical field of power generation control, and the system comprises a multi-source data collection module which carries out the real-time parallel collection of all-dimensional operation parameters through a sensing network and unit decentralized control system interface disposed at a key node, and builds a multi-modal time sequence data flow; according to the method, a foresight control strategy is formed by constructing a fusion prediction model, sensing the running state of a unit in real time and predicting the change trend of key parameters, the defect of response lag of a traditional system is effectively overcome, and the purposes of accurate load tracking and advanced regulation and control under the working condition of deep peak regulation are achieved; a global optimization decision-making mechanism is established by adopting a deep reinforcement learning algorithm, optimal control parameters are calculated in real time through the intelligent peak regulation module, a boiler, a steam turbine and an environmental protection system are dynamically coordinated, the problem of insufficient stability caused by subsystem independent control is solved, and the optimal balance of safety, stability and economic benefits is achieved.

The invention discloses a fuzzy model predictive control method for a coal-fired boiler-steam turbine system, and mainly relates to the technical field of intelligent environmental protection. Comprising the following steps: S1, constructing a fuzzy prediction model by using Takagi-Sugeno fuzzy logic; s2, constructing a control efficiency evaluation index, and establishing a dual-channel event triggering mechanism; s3, constructing a model prediction controller, constructing an objective function based on the prediction model, and solving an optimal control signal at each sampling moment; s4, performing offline training on the fuzzy prediction model through actual data of the boiler-steam turbine system to obtain a prediction model for a control system; s5, on the basis of a dual-channel event triggering mechanism, updating the prediction model according to real-time data through an online updating strategy; according to the method, the steam drum pressure, the generated power and the steam drum water level can be efficiently and accurately controlled, the calculation overhead can be effectively reduced, and the real-time performance and the stability of a control system are improved.