5839 results about "Generating unit" patented technology

The invention relates to the technical field of fault detection, and discloses a diesel generating set fault detection method and system based on deep learning, and the method comprises the steps: obtaining first vibration signal data, and carrying out the time-frequency decomposition, and obtaining a dynamic change feature; de-noising processing is carried out on the dynamic change features to obtain a time-frequency feature sequence; extracting a peak energy distribution data set, and calculating each frequency band entropy value to obtain a frequency band entropy value sequence; classifying the frequency band entropy sequence, determining a random fluctuation reference mode, and separating to obtain an abnormal frequency component; calculating a spectral line spacing and amplitude ratio, obtaining a spectral line feature data set, classifying the spectral line feature data set, and determining a fault classification result; obtaining current second vibration signal data, performing similarity calculation on the current second vibration signal data and a pre-established normal mode library, and outputting a fault feature vector; and verifying the fault feature vector to obtain a final fault detection result. According to the method, closed-loop diagnosis from signal acquisition to fault classification can be realized, and the fault detection precision of the diesel generating set is improved.

The invention discloses a fan blade state monitoring method based on multi-sensor fusion, relates to the technical field of wind power, and is suitable for wind energy prime mover equipment manufacturing and blade state monitoring technologies of onshore and offshore wind generating sets. The method comprises the following steps: acquiring operation data, a vibration signal, an acoustic signal and a pulse signal of a fan; the current working condition state of the fan is recognized, common-mode fault verification, local damage positioning and transient stress damage analysis are carried out on the vibration signals and the acoustic signals, and a fault analysis result and a first damage analysis result are obtained; performing phase-locked amplification analysis on the vibration signal and the acoustic signal through active excitation to obtain a second damage analysis result; and finally, a comprehensive state monitoring report of the fan blade is generated, so that the problems of difficulty in identification of weak damage and high false alarm rate of blades of land and offshore wind generating sets in wind energy prime mover equipment manufacturing under a non-stable working condition are solved, and the equipment operation and maintenance intelligent level in the wind energy prime mover equipment manufacturing industry is effectively improved.

The invention relates to the technical field of power system operation and control, and discloses a primary and secondary frequency modulation cooperative control system of a hybrid energy storage coupling wind generating set, which comprises a wind power generation unit, a hybrid energy storage unit and a central cooperative controller. A total power demand including inertia response and primary and secondary frequency modulation is synthesized, a primary and secondary frequency modulation cooperative distribution module generates a dynamic adjustment weight by using an S-type nonlinear function based on a frequency change rate and frequency deviation coupling relationship, and an energy relay compensation mechanism is introduced to fill a power gap in a switching process. And the SOC adaptive constraint and execution module applies direction selective boundary constraint to the state of charge, and controls hybrid energy storage to perform internal energy self-balancing in a frequency modulation dead zone. According to the invention, seamless connection of multi-time scale frequency modulation is realized, frequency secondary drop is effectively prevented, and the frequency support capability and the self-recovery capability of the system are improved.

The invention discloses a dynamic monitoring method and system for settlement and inclination of a tower drum of a wind generating set, and relates to the technical field of safety monitoring of wind power generation infrastructure, the method comprises the following steps: synchronously collecting inclination data and positioning data of each monitoring point, and carrying out space-time alignment to obtain a fusion data set; decoupling the dynamic elastic response of the tower drum and the steady-state deformation of the foundation from the fused data through frequency domain analysis, and further calculating the overall inclination rate, the settlement amount and the non-uniform settlement rate of the tower drum; performing safety assessment based on the calculated parameters and a preset safety threshold, and determining a basic safety state and a risk mode; and finally, generating graded early warning information and decision information including risk positioning and trend prediction according to an evaluation result. Through the above mode, the method achieves the precise separation and monitoring of the dynamic deformation characteristics of the tower drum, improves the accuracy of safety evaluation and the timeliness of early warning, and provides an effective data support for the operation and maintenance decision of a wind generating set.

The invention discloses a multi-energy-storage thermal power generating unit load prediction and optimal scheduling method and system, and relates to the technical field of multi-energy-storage thermal power generating units, and the method comprises the steps: collecting the operation parameters and external environment parameters of a thermal power generating unit in real time, and constructing a real-time state parameter matrix; constructing a load prediction model based on the historical state parameter matrix, importing the real-time state parameter matrix into the load prediction model, outputting a load trend prediction curve, and triggering an early warning signal through a secondary discrimination mechanism; identifying a load disturbance value based on the load trend prediction curve, obtaining a load disturbance sequence, and decoupling the load disturbance sequence into a plurality of components; inputting the plurality of vectors into a preset decision network, dynamically correcting a constraint condition built in the decision network in combination with the early warning signal, introducing an improved dragonfly algorithm for optimization iteration, and generating an optimization scheduling instruction; according to the method, the adaptability of optimal scheduling and high-precision prediction of the load trend are improved.

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 fusion power generation system, a power generation control method, a storage medium and a controller, and relates to the technical field of fusion energy. The fusion power generation system comprises a steam generator set, a plurality of Tokamak devices and a plurality of thermal conversion units, the Tokamak devices and the thermal conversion units are in one-to-one correspondence, each thermal conversion unit is provided with a first channel and a second channel, and the Tokamak devices and the first channels of the corresponding thermal conversion units form a cladding cooling loop. The steam generator set and a plurality of second channels connected in sequence form a power generation loop; wherein the plurality of Tokamak devices are configured to operate in an alternating or complementary manner; the thermal conversion units are configured to receive heat from the corresponding cladding cooling loops and convert working media in the power generation loops into steam through the heat so as to drive the steam generator set to generate power. According to the system, the plurality of Tokamak devices operate in an alternating or complementary mode, so that heat loss can be reduced, the power generation efficiency is improved, and the plasma control difficulty is reduced.

This invention discloses a supercritical carbon dioxide cycle generator set water spray desuperheating system, comprising a supercritical carbon dioxide cycle power generation system and a water spray desuperheating system; the supercritical carbon dioxide cycle power generation system includes a heater, a screen-type superheater, a final-stage superheater, and a turbine; the water spray desuperheating system includes a first desuperheating water injection point, a second desuperheating water injection point, and a liquid-water separation system; the heater outlet is sequentially connected to the turbine inlet via the first desuperheating water injection point, the screen-type superheater, the second desuperheating water injection point, and the final-stage superheater; the turbine outlet is connected to the inlet of the liquid-water separation system; the liquid outlet of the liquid-water separation system is connected to the first and second desuperheating water injection points; and the gas outlet of the liquid-water separation system is connected to the heater inlet. This system can solve various problems caused by carbon dioxide desuperheating.

The invention relates to the technical field of generator set intelligent control, and discloses a generator set intelligent control method and system, and the method comprises the steps: obtaining the sensor data and vibration signals of a generator set; obtaining a corrected frequency characteristic value according to sensor data screening, denoising and frequency characteristic correction; generating and iteratively updating a control decision instruction sequence according to the real-time change of the vibration signal and the corrected frequency characteristic value to obtain a system stability index; and combining system stability index feedback adjustment to obtain a control decision reliability index. The method can solve the problem of noise interference under a dynamic working condition, realizes fault early warning, parameter optimization and system stability, and improves energy efficiency and operation reliability.

The invention discloses a multi-objective collaborative optimization control method for a new energy station and an energy storage system, relates to the technical field of new energy optimization control, and constructs a collaborative optimization framework with multi-time scale, multi-objective and multi-element deep coupling. The framework realizes joint optimization control of a wind power plant, a photovoltaic power station, an energy storage system and a conventional generator set through a whole process design of target modeling-scene adaptation-algorithm solution-closed loop execution. Formulating a source network storage dynamic interaction strategy based on scene self-adaption, and fully mining the adjustment potential of wind power, photovoltaic, energy storage and conventional generator sets; and solving a real-time optimal control distribution value by adopting a multi-objective optimization algorithm to form closed-loop coordination control. According to the method, the problems of poor adaptability and insufficient source network storage resource collaboration of traditional single target optimization are solved, the new energy consumption rate and the system stability are remarkably improved, and the operation cost is reduced.

The invention provides an analysis method and device for flow, efficiency and water consumption rate of a hydraulic power plant generator set. A distributed flow measurement unit based on a domestic PLC controller and a domestic operating system is constructed, and each unit is independently configured with the flow measurement unit to realize decentralization of data acquisition and processing; active power, guide vane opening, water head difference, instantaneous flow and volute inlet pressure data are collected in real time through a distributed flow measurement unit, and a unit efficiency and water consumption rate calculation model is dynamically fitted based on the data; sending an output result of the calculation model to a monitoring system through an anti-interference communication network, wherein the communication network adopts layered wiring and a double-shielded twisted pair to reduce the signal bit error rate; and the IMC integrated management and control platform is used for remote monitoring and diagnosis of the flow measurement unit, and seamless connection with a smart power plant data medium station is realized. The system reliability and the maintenance flexibility are improved, and the autonomous controllable requirements of domestic substitution and intelligent power plants are comprehensively met.

The invention relates to the technical field of generator state monitoring, in particular to a leakage detection method and system for an ORC generator set, and the method comprises the steps: firstly, synchronously collecting system key operation parameters and environment concentration data; then, matching the pressure value with a pre-generated and load-divided leakage-free reference model, and calculating a theoretical pressure value and a real-time deviation; and a three-dimensional state judgment matrix is innovatively constructed and applied to perform combined logic judgment on a pressure deviation level and an environment concentration level, so that step-by-step diagnosis from micro-leakage early warning to serious leakage alarm is realized. After the leakage is confirmed, the leakage rate can be estimated, and the possible leakage area can be positioned in an assisted manner. According to the method, early-stage, sensitive, automatic and intelligent detection and diagnosis of leakage of the ORC generator set are realized, and the operation safety and the maintenance efficiency of the set are remarkably improved.

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 day-ahead market scheduling optimization method for power balance characteristics in an embedded scheduling time period, and the method comprises the following steps: 1), constructing an actual output expression and a net load prediction power expression of a generator set based on an asymmetric affine strategy; 2) based on the opportunity constraint optimal power flow, constructing a day-ahead market economic dispatching model of power balance characteristics and uncertainty in an embedded dispatching time period; 3) analyzing and converting the day-ahead market economic dispatching model with the power balance characteristics and uncertainty in the embedded dispatching time period, and constructing a day-ahead market safety constraint economic dispatching model with the power balance characteristics in the embedded interval; and 4) solving the day-ahead market security constraint economic dispatching model embedded with the power balance characteristics in the interval to obtain a node marginal price, and outputting a market dispatching scheme with the minimum node marginal price. According to the method, on the basis of considering the uncertainty of the net load prediction error, the power transmission risk cost caused by the uncertainty can be effectively internally reduced.

The invention belongs to the field of automatic control of hydroelectric generating sets, and particularly discloses a primary frequency modulation optimization control method and system based on power opening nonlinear prediction.The method comprises the steps that frequency deviation is converted into primary frequency modulation power variable quantity, the power variable quantity and a basic power set point of a set are added, and a dynamic power target is obtained; integrating the power deviation signal to obtain a power integration opening reference instruction; taking the dynamic power target and the unit water head as input of a feed-forward model, and obtaining a feed-forward dominant opening instruction; the opening degree deviation value is input into a PID controller, and a feedback opening degree correction instruction is generated; and a guide vane opening given value is obtained based on the feed-forward dominant opening instruction and the feedback opening correction instruction and serves as a given signal of a guide vane position control loop. According to the invention, through nonlinear prediction and a unique feedback structure, high self-adaption to the working condition change of the unit is realized, and the rapidity, consistency and robustness of the primary frequency modulation response of the unit are remarkably improved.

The invention discloses an intelligent monitoring and evaluating system for the metal health state of a generator set, and belongs to the technical field of state monitoring of power generation equipment. The system comprises a data acquisition and preprocessing module, a data fusion and feature extraction module, a metal health state evaluation module, a residual life prediction and fault tracing module and a visual intelligent decision support module. The method comprises the following steps of: extracting cross-scale damage characteristics by fusing macroscopic operation data and microscopic nondestructive testing signals; calculating a comprehensive health index by adopting a physical mechanism model and data-driven model adaptive weighted fusion mode; dynamic residual life prediction and failure reason intelligent traceability are realized; and finally, graded early warning and maintenance decision suggestions are provided through a three-dimensional visual interface. According to the method, the problems of single monitoring dimension, model isolation and static prediction in the prior art are solved, and comprehensive, high-precision and interpretable evaluation and predictive maintenance support of the health state of the metal part are realized.

A vibration damping device for a head-up display driving module, the device comprising: a power generating unit configured to a first damper having a predetermined thickness based on a shape corresponding to a motor mount to which a motor is fixed and a second damper fitted into an open hole of a damper mount disposed on top of the motor mount; and a power transmission unit configured to transmit power of the motor by rotating a lead screw extended and coupled to a rotating shaft of the motor.

The invention discloses a regional power grid new energy consumption method and system based on computing power-power space-time coordination. The method comprises the following steps: acquiring real-time operation state data of a regional power grid and to-be-processed computing power task data of a data center cluster; dividing the computing power task into flexible loads based on the time sensitivity of the task, and determining the energy consumption conversion relation of the flexible loads; on the basis of the real-time operation state and the energy consumption conversion relation, the cross-regional migration amount of the flexible load and the output state of the generator set serve as decision variables, and a cooperative scheduling instruction containing a computing power task cross-regional migration path and generator set power adjustment is generated; and in response to the instruction, the flexible load in the load center area is migrated to the data center for execution in a cross-area manner through the communication network, and the output of the generator set in the corresponding area is synchronously adjusted. The method is used for solving the problems that in the prior art, due to the fact that a physical power transmission channel is limited, new energy power abandoning is serious, and power loads and new energy resources are mismatched in space distribution.

The invention discloses a wind generating set transmission chain fatigue load prediction method and system considering sandstorm characteristics, and belongs to the technical field of wind power generation and structure fatigue prediction. According to the method, a wind speed time sequence capable of representing sandstorm evolution characteristics is obtained and serves as external physical excitation to be input into a wind-machine-electricity coupling state space model, and a dynamic torque time sequence of a transmission chain low-speed shaft is obtained through calculation; on the basis, a load spectrum is generated by adopting a rain flow counting method, and the accumulated fatigue damage degree corresponding to the sandstorm event is calculated in combination with the Miner linear accumulated damage criterion and the S-N curve of the low-speed shaft material; and further comparing the damage degree with a preset threshold value, and when the damage degree exceeds the threshold value, automatically generating a preventive active load reduction control strategy aiming at the sandstorm, thereby realizing a closed loop of prediction and control. According to the method, the influence of extreme non-stable wind conditions such as sandstorm and the like on the fatigue damage of the transmission chain can be quantitatively evaluated, and technical support is provided for safe operation and predictive maintenance of a wind turbine generator in extreme weather.

The invention discloses a hydro-generator magnetic pole cooling fin tool configuration method and system based on a graph neural network, and belongs to the technical field of hydro-generator assembly process intelligence. The problem of intelligent upgrading of hydro-generator magnetic pole cooling fin tool configuration is solved. The method comprises the following steps: data acquisition: acquiring surface temperature field distribution data, deformation parameter data and three-dimensional vibration spectrum data of the magnetic pole cooling fin, and microscopic morphology image data of a contact area of the magnetic pole cooling fin and a clamp; constructing a node feature vector of a topological graph structure comprising a magnetic pole cooling fin node, a clamp node and an environmental parameter node, and generating a topological graph comprising node features and edge weights by using a graph convolutional neural network; calculating fixture positioning probability distribution, and outputting an optimal tool combination scheme; and executing the physical assembly instruction to complete the configuration of the hydro-generator magnetic pole cooling fin tool. The configuration efficiency of the hydro-generator magnetic pole cooling fin tool is improved.

The embodiment of the invention provides a load balancing control method of a variable pitch system, which comprises the following steps of: continuously acquiring blade root bending moment and rotor azimuth angle signals, accurately preprocessing to obtain 1P harmonic information of bending moment in a flapping direction, and updating accumulated wear conditions of each blade under different azimuth angles in real time based on the 1P harmonic information. According to the method, a dynamic abrasion map is established, the active balance variable pitch offset is actively calculated based on the abrasion map, the load is intelligently guided from a heavily-abraded area to a lightly-abraded area, and a refined blade variable pitch angle is finally formed in combination with traditional IPC correction and a collective variable pitch instruction. In this way, key components such as the variable pitch bearing are prevented from bearing overhigh local stress for a long time in a specific azimuth angle, uniform abrasion of rolling bodies or raceways is achieved, and therefore local fatigue damage is remarkably reduced, and the service life of the variable pitch bearing of the wind generating set and the service life of related components are prolonged.

The invention discloses a coal-fired unit low-carbon operation output optimization method and system suitable for low-carbon transformation, and the method comprises the steps: selecting a to-be-studied biomass blending combustion coal-fired coupling carbon capture generator set under coal-electricity low-carbon transformation, and obtaining the related data of a transformed coal-fired unit; a mechanism-data hybrid driven modeling method is adopted, and a mechanism model of the biomass blending combustion coal coupling carbon capture unit obtained after coal-electricity low-carbon transformation is constructed; constructing a low-carbon economic objective function of the biomass blending combustion coal coupled carbon capture generator set after coal-electricity low-carbon transformation, and constructing a calculation model of related low-carbon economic parameters in the objective function; constructing constraint conditions of a biomass blending combustion coal coupling carbon capture generator set after coal-electricity low-carbon transformation, and constraining input and output variables of the mechanism model at the same time; and an optimal low-carbon economic operation output scheme under the scene uncertainty is analyzed and considered, and an optimization result of the operation output of the biomass blending combustion coal coupled carbon capture generator set after coal power low-carbon transformation under the scene uncertainty is obtained through a mode of minimizing an objective function. According to the method, guidance can be provided for the operation output of the biomass blending combustion coal coupling carbon capture power station in each time period in the day.

The invention discloses a power coordination control method of a high-temperature gas cooled reactor nuclear steam supply system, which relates to the technical field of nuclear power, and comprises the following steps of: coupling multiple modules in the high-temperature gas cooled reactor nuclear steam supply system through a common conventional island; the key state parameters of the to-be-adjusted module are used as main control variables, and the other modules are used as auxiliary control variables, so that the mutual influence relationship among the modules can be comprehensively considered; reasoning the control quantities based on a preset fuzzy rule to determine a fuzzy control strategy, so that adverse effects among modules can be counteracted, overall parameters are kept in a design value range, and safe and stable operation of the system is guaranteed; flexible adjustment can be performed according to key state parameters of different modules by using a fuzzy control strategy, the power of the reactor is quickly and accurately controlled, the dynamic response capability of the system is improved, and the requirement that the power of the reactor is quickly adjusted along with the load requirement of the steam turbine generator unit is met.

The invention relates to the technical field of motor detection, in particular to a generator set fault diagnosis and detection method based on deep learning, and the method comprises the steps: firstly, synchronously collecting three-phase voltage, current and rotating speed signals, and constructing a multi-dimensional time sequence matrix through data cleaning and sliding window segmentation; then, carrying out multi-scale decomposition on the matrix by adopting adaptive wavelet packet transformation, combining each frequency band reconstruction coefficient with an original signal channel, and constructing an enhanced feature tensor; then, a CNN-BiLSTM parallel network is constructed; and finally, dynamically fusing the features of the two branches through a self-adaptive weighted fusion strategy, and inputting a multi-layer full-connection classifier to output a fault type. According to the method, early weak fault features are effectively enhanced, bearing faults, rotor eccentricity, electrical imbalance and composite faults thereof can be accurately recognized, the intelligent level and accuracy of fault diagnosis of the generator set are remarkably improved, and the method can be widely applied to online monitoring and health management of power generation equipment of a power system.

The invention relates to a transmission device, a transmission system, a wind generating set and a maintenance method, the transmission device comprises a shafting assembly and an interference magnitude adjusting device, the shafting assembly comprises a main shaft and a bearing, the bearing is arranged around the main shaft, an inner ring of the bearing is in interference fit with the main shaft, and the main shaft is provided with a hollow cavity. The interference magnitude adjusting device is arranged in the hollow cavity and used for applying acting force to the inner wall face, defined by the main shaft, of the hollow cavity, so that the main shaft deforms to adjust the interference fit amount between the main shaft and the inner ring of the bearing. The bearing ring running probability can be reduced, and the power generation benefit of the wind generating set is guaranteed.

The invention belongs to the technical field of electric power peak regulation and energy distribution, and discloses a thermal power generation energy storage system based on heat storage and energy storage cooperation and an operation control method thereof. The thermal power generation energy storage system comprises a thermal generator set unit, a fused salt energy storage unit, a storage battery energy storage unit and a control unit, and the control unit is used for controlling the storage battery energy storage unit and the fused salt energy storage unit to store energy when a power grid is in a low ebb or new energy output is excessive; when the power grid is in a peak, the storage battery energy storage unit and the fused salt energy storage unit are controlled to release energy; when the storage battery energy storage unit and the fused salt energy storage unit are controlled to release energy, fused salt in the high-temperature tank is preferentially scheduled to generate steam through the second heat exchanger, and then the storage battery energy storage unit and the fused salt energy storage unit are scheduled to respond according to the fluctuation condition of the power grid. According to the invention, fused salt heat storage and battery energy storage are used for complementary peak regulation, and efficient, flexible, economical and safe peak regulation of the power system is realized.

The invention relates to a fused salt heat storage system based on heat energy grading matching. The system comprises a first-stage heat exchange unit, a second-stage heat exchange unit, a third-stage heat exchange unit and a mixing unit, and the first-stage heat exchange unit comprises a first-stage fused salt heat storage loop and a first-stage heat exchange adjusting valve and is used for absorbing and storing high-grade heat of exhaust gas of an exhaust pipeline of a boiler furnace; the second-stage heat exchange unit comprises a second-stage fused salt heat storage loop and a second-stage heat exchange regulating valve and is used for absorbing and storing high-grade heat of main steam extraction of a main steam extraction pipeline of a high-pressure cylinder of the steam turbine; the third-stage heat exchange unit comprises a third-stage fused salt heat storage loop and a third-stage heat exchange regulating valve and is used for absorbing and storing low-grade heat of air exhaust of an intermediate-pressure cylinder of an air exhaust pipeline of the intermediate-pressure cylinder of the steam turbine; the mixing unit mixes the three kinds of exhaust heat and outputs working medium fluid meeting the target temperature so as to adapt to different preset operation working conditions of the thermal power generating unit. Therefore, heat energy can be stored and released in a gradient mode through the system, wide-temperature-range efficient utilization is achieved, and the flexibility and energy efficiency of the thermal power generating unit are improved.

The invention discloses a titanium alloy skin processing compensation method based on a digital twinning residual stress prediction model, particularly relates to the field of aeronautical manufacturing, and aims to solve the problems that local resilience is difficult to prejudge and a compensation result is unstable due to inconsistent stress release time sequences and dispersed compensation basis in a subunit cutting process of a titanium alloy skin. A unit stress release state is constructed by collecting a unit contour offset and a unit cutting sequence, same-chain deduction is carried out by combining preorder unit residual stress mapping to generate a unit compensation candidate quantity, and execution judgment and a closed-loop updating parameter layer are formed based on playback and re-scanning consistency analysis. According to the method, compensation decision traceability, processing deviation convergence and continuous inheritance between working steps are achieved, the manual repeated trial cutting and parameter adjustment cost is reduced, and the transition smoothness of adjacent units and the forming consistency of the whole skin are improved.

The invention relates to the technical field of electric power generation equipment monitoring, in particular to an intelligent multi-point monitoring method and system for a generator set. The method comprises the following steps: acquiring data of a generator set, and dividing the generator set into a primary monitoring sub-region and a secondary monitoring sub-region; deploying multiple types of sensors according to monitoring requirements of key components of each monitored sub-region, and collecting multi-dimensional parameters of the sub-regions in real time; the multi-dimensional parameters of the sub-regions are analyzed in real time according to the multi-dimensional parameters, power generation grid connection abnormal conditions are identified, and multi-level warning and abnormal positioning are carried out; the system comprises a multi-point region division module, a multi-dimensional data monitoring module and a power generation grid-connected abnormity warning module. By means of the mode, the abnormal recognition efficiency and adaptability are improved, and the operation safety and grid connection reliability of the generator set are improved.

The invention relates to the technical field of peak regulation of coal-fired power units, and discloses a self-adaptive regulation method and system for full-load peak regulation of a coal-fired power unit. The method comprises the steps of collecting unit operation parameters such as boiler temperature, turbine rotating speed and generator voltage, and power grid peak regulation instructions such as real-time load demand and predicted load fluctuation; analyzing a peak regulation state based on the collected data, and dividing the peak regulation state into three types of stable operation, transition regulation and limit peak regulation; then calculating an adjustment characteristic quantity according to the current state and the operation parameters, wherein the characteristic quantity reflects the matching relationship between the unit performance and the peak regulation requirement; generating a plurality of groups of adjustment schemes including combustion optimization, steam adjustment and power control based on the characteristic quantity and the peak regulation instruction; and selecting and executing an optimal scheme by evaluating indexes such as efficiency loss, stability influence and maintenance cost. The method can dynamically respond to the load change of the power grid, accurately adapt to the peak regulation requirement in the full load range, and enable the peak regulation of the unit to be more flexible and harmonious.