19 results about "Energy flow analysis" patented technology

The invention relates to the technical field of motor fault diagnosis, and discloses a multi-degree-of-freedom resonant excitation motor dynamic vibration test system and a test method, the system injects a specific harmonic current into a motor through closed-loop control and calculation and a high-bandwidth harmonic injection driver, so that the actual vibration of the tested motor tracks a preset target vibration profile in real time. In the testing process, the cross-spectral density of multi-point vibration signals is analyzed, and a transmission path and a collection area of vibration energy in a motor structure are calculated; and meanwhile, the electromagnetic impedance and the mechanical impedance of the motor are identified and decoupled on line by superposing a broadband disturbance signal in the driving current. In combination with energy flow analysis and an impedance decoupling result, the method can accurately position a vibration abnormal position, clearly causes whether a fault source is from mechanical structure characteristic change or electromagnetic part performance change from a physical level, and realizes deep and accurate diagnosis of the dynamic characteristics of the motor.

The invention relates to the technical field of coal-fired unit energy flow analysis and prediction, in particular to a coal-fired unit boiler energy flow analysis and prediction method under rapid variable load, which specifically comprises the following steps of: firstly, combining a thermodynamic physical framework with a recurrent neural network, and representing a function relationship between a time-varying parameter and a state variable in a mechanism model through a neural unit; rapid fluctuation of energy in the boiler is accurately captured; secondly, a multi-mode switching strategy based on an attention mechanism is introduced, flexible switching is carried out between a strong coupling state and a weak coupling state, and the prediction precision under high-speed load change is guaranteed; and finally, introducing an error compensation model, and dynamically correcting a hybrid model prediction residual error. According to the method, physical constraints of mechanism modeling, multi-mode switching of an attention mechanism and an error compensation model are integrated and fused, so that the problems that most of hybrid modeling studies in the prior art mainly focus on steady-state or finite transient prediction, and studies on energy flow dynamic characteristics under rapid load change are still relatively deficient are solved.

The patent application discloses a photovoltaic power generation carbon footprint modeling method and system fusing supply chain and energy flow analysis, and particularly relates to the technical field of environmental management. A fine mapping relationship between a photovoltaic power station and components is established, real scene data sources are determined, based on the system boundary and functional unit of the photovoltaic component product, localized real scene data is obtained; a time scale photovoltaic component correction coefficient is constructed, and then a long time sequence real scene data list is obtained; the constructed real scene data list is fused with an international product carbon footprint background database to obtain localized photovoltaic product carbon footprint data with spatial and temporal resolution; the energy flow of the photovoltaic power station is tracked, and a photovoltaic power generation power balance and loss model is constructed; combined with the construction list and operation data of other components of the photovoltaic power station, the localized site scale photovoltaic power generation carbon footprint data is formed. The technical scheme solves the problem of the existing photovoltaic power generation carbon footprint evaluation method being too static and lacking accuracy, and realizes accurate and dynamic quantification of the photovoltaic power station carbon footprint.

This invention relates to an optimization method for an electric-gas coupled system based on adaptive piecewise linearization. This invention considers the coordinated operation of the power system and the natural gas system, and can improve the overall efficiency of the energy system through multi-energy complementarity, promote the absorption of new energy sources, and simultaneously improve the safe and reliable supply of electricity and natural gas. In the calculation process, the number of segments in the linearized pipeline airflow equation obtained through piecewise linearization is adaptively determined. Specifically, the number of segments and segmentation points are dynamically divided using an iterative method, gradually increasing the number of segments and segmentation points. This approach, while ensuring computational accuracy, introduces the minimum number of segmentation intervals and determines the optimal segmentation point location. This transforms the optimal energy flow calculation of the electric-gas coupled system into a mixed-integer linear programming model, achieving an effective trade-off between solution accuracy and computational efficiency. Ultimately, it provides a feasible and efficient technical means for the optimal energy flow analysis of electric-gas coupled systems.

The application provides a two-stage electric-thermal coupling system energy flow calculation method and system based on hybrid driving, belongs to the technical field of energy flow calculation of comprehensive energy systems, and comprises the following steps: constructing a heterogeneous graph structure for the electric-thermal coupling comprehensive energy system, and building heterogeneous graph data based on the characteristics of the heterogeneous graph structure; inputting the heterogeneous graph data into a graph neural network model based on a relationship-aware grouping graph attention mechanism; taking the prediction result output by the graph neural network model based on the relationship-aware grouping graph attention mechanism as an initial value, and quickly correcting the initial value; and outputting complete system multi-energy flow analysis results based on the correction result.

The application discloses a pure electric light truck whole vehicle energy flow optimization method, device, equipment and medium. The method comprises the following steps: acquiring random working condition input parameters, performing Monte Carlo simulation according to the random working condition input parameters and a pre-constructed whole vehicle energy flow analysis model to obtain working efficiency statistical data of each energy consumption component of the whole vehicle; identifying working condition associated components based on the working efficiency statistical data, calculating energy consumption influence indexes of the working condition associated components based on preset dot matrix graph rules; and determining a component energy efficiency optimization strategy of the pure electric light truck according to the energy consumption influence indexes. The energy efficiency optimization pertinence is improved, the whole vehicle energy efficiency level of the pure electric light truck is improved, and the overall efficiency of energy flow analysis and optimization is improved.

This invention relates to the field of energy flow analysis and optimization technology for turbocharged engines, and discloses a full-process energy control method for turbocharged engines. First, based on the energy balance and mass balance equations of the two-stage turbocharger system and the bypass valves at the turbine and pressure ends of the high-pressure stage, a basic thermodynamic state calculation equation for the gas path is established. Then, the state parameters of the working gas in the external gas path are calculated using input and control parameters, and the state parameter values ​​at each degree of crankshaft rotation within the cylinder are calculated. These state parameters are then connected to obtain a complete full-process indicator diagram. Finally, the full-process indicated work is obtained by integrating the full-process indicator diagram. Furthermore, a distribution diagram of the full-process indicated work as a function of control parameters is obtained, and the optimization range of the control parameters corresponding to the optimized indicated work is derived from the distribution diagram, thus providing an indicative constraint range for the control of the indicated work.

The invention provides a method for reconstructing a safe and efficient operation domain of a gas turbine driven supercharging system, and the method comprises the steps: firstly, carrying out the energy flow analysis of a built supercharging system-load steady state matching energy flow analysis model, and obtaining supercharging system-load energy flow characteristics; performing simulation operation on the built pressurization system-load transient matching point migration model to obtain an operation point migration rule of the pressurization system-load under a transient working condition; then, on the basis of the supercharging system-load energy flow characteristics, the feasible operation domain of the supercharging system-load is reconstructed, and a steady-state operation domain of the supercharging system-load is obtained; and according to the running point migration rule under the transient working condition, reconstructing the feasible running domain of the pressurization system-load to obtain a transient running domain of the pressurization system-load. According to the method, the steady-state operation domain and the transient operation domain corresponding to the gas turbine driving supercharging system can be accurately reconstructed, and a decision basis is provided for efficient operation and safe operation under subsequent full working conditions.

The invention discloses an industrial chain characterization method based on a complex network theory and considering an energy network, and the method comprises the steps: abstracting an enterprise covering core product transaction into a network node, and constructing an initial directed network of a coupled material flow-energy flow; network edges are weighted based on material flow and energy flow analysis, and a weighting system comprehensively considering transportation parameters and waste heat and waste energy utilization is established; establishing a four-dimensional scoring function fusing product compatibility, energy complementarity, geographical proximity and industry chain relevance, and implementing a differential supervised edge adding mechanism; constructing a small world characteristic verification index system, and judging topological characteristics of the reconstructed network; and an iterative tuning mechanism is established, and small-world characteristic representation is realized through a clustering enhancement or path shortening strategy. According to the method, the industrial chain network is constructed by unifying the material flow and the energy flow, cross-level cooperation and same-level linkage opportunities are accurately identified, intelligent reconstruction of a small world network is realized, and the method is of great significance to energy conservation, consumption reduction and layout optimization of the industrial chain.

A vehicle energy flow analysis method and apparatus, a device, and a storage medium. The method comprises: a processing device acquiring data to be processed, wherein the data to be processed comprises a plurality of data files, each data file is collected from a sensor, and because the sensors have different sampling frequencies, the number of data contained in each data file is also different; on the basis of a data file obtained by the sensor having the highest sampling frequency, determining data corresponding to each moment in other data files; and then performing energy flow analysis on the basis of data in all the data files corresponding to the same moment. The method can implement effective analysis of collected data, thereby reducing deviations from an actual test result.

The invention belongs to the technical field of urban rail transit operation and maintenance, and discloses a metro vehicle abnormal jitter repairing method, system, device and medium, and the method comprises the steps: 1, collecting a vehicle body vibration signal, fusing passenger comfort feedback, and constructing a vehicle body abnormal jitter grading system related to objective indexes and subjective feelings; secondly, collecting static environment parameters and vehicle running dynamic environment parameters around the track, building a multivariable regression model, and quantifying the influence weight of each parameter on jitter; thirdly, main environmental factors are found out according to the influence weights, key vibration transmission points are determined through simulation of a vehicle body-track rigid-flexible coupling model and energy flow analysis of a vehicle body-bogie finite element model, and a fault source is positioned; and 4, generating a temporary protection and warehousing repair scheme according to the fault source, the temporary protection scheme being a speed adjustment curve optimized by a genetic algorithm, and the warehousing repair scheme being a personalized operation instruction based on a mapping library. The method can accurately diagnose the abnormal jitter reason of the vehicle body and generate an efficient repair scheme.

The invention discloses a gas network global linearization port model-based electricity-gas energy flow rapid analysis method, which comprises the steps of firstly establishing a global linearization port model of a natural gas network, then identifying key parameters of the port model by adopting a machine learning method, and finally realizing efficient electricity-gas energy flow analysis based on the gas network port model. According to the method, systematic variable elimination and order reduction are carried out on a whole-network dynamic equation, key parameters are identified in combination with a data driving method, and a global linearization port model which is efficient in calculation and can accurately represent the external dynamic characteristics of the complex gas network is obtained; the method can effectively solve the core problems that traditional energy flow calculation efficiency and calculation precision are difficult to give consideration to and dependence on internal complete information is high, so that efficient and high-precision dynamic energy flow calculation of the electricity-gas comprehensive energy system is achieved, and the practicability and timeliness of analysis and decision making of a large-scale energy system are remarkably improved.

The invention discloses a vehicle energy flow analysis and endurance simulation method, device and equipment and a storage medium, relates to the technical field of simulation testing, and discloses a vehicle energy flow analysis and endurance simulation method, which comprises the following steps: constructing a parameterized whole vehicle simulation model based on vehicle system parameters and a preset component library; responding to the user scene combination instruction, and generating a multi-scene simulation task based on the working condition configuration information; acquiring gradient information, whole vehicle mass, a rolling resistance coefficient and aerodynamic parameters input by a user to obtain resistance calculation parameters; simulating the parameterized whole vehicle simulation model based on the resistance calculation parameter and the multi-scene simulation task to obtain simulation result data; and performing energy flow analysis and endurance evaluation based on the simulation result data to obtain a simulation analysis report. According to the scheme, full-process automation can be achieved in the vehicle energy flow analysis and endurance simulation process, and the simulation efficiency is improved.

The invention provides a two-stage electrothermal coupling system energy flow calculation method and system based on hybrid drive, and belongs to the technical field of comprehensive energy system energy flow calculation, and the method comprises the steps: constructing a heterogeneous graph structure for an electrothermal coupling comprehensive energy system, and building heterogeneous graph data based on the characteristics of the heterogeneous graph structure; inputting the heterogeneous graph data into a graph neural network model based on a relation perception grouping graph attention mechanism; taking a prediction result output by the graph neural network model based on the relation perception grouping graph attention mechanism as an initial value, and quickly correcting the initial value; and outputting a complete system multi-energy flow analysis result based on the correction result.

The application provides an AI-based carbon asset and carbon verification management method and platform, belonging to the technical field of carbon emission management. The method comprises: inputting operation activity data of a target object into a preset energy efficiency analysis model to obtain an energy efficiency analysis result; based on the energy efficiency analysis result, performing energy flow modeling and analysis on the operation activity data of the target object to obtain an energy flow analysis result; inputting the energy flow analysis result into a preset energy efficiency balance optimization model to obtain an optimized energy distribution scheme and predicted carbon emission values of each link based on the energy distribution scheme, wherein the energy efficiency balance optimization model is configured to optimize energy distribution with the goal of minimizing total carbon emissions under the production constraint conditions of the target object; comprehensively calculating the predicted carbon emission values of each link to obtain a predicted total carbon emission value of the target object; and generating a corresponding target carbon asset management strategy according to the predicted total carbon emission value, carbon trading market data and carbon sink data.

The application provides a reconstruction method of a gas turbine driven supercharging system operation domain, in which firstly, through energy flow analysis on a constructed supercharging system-load steady-state matching energy flow analysis model, the energy flow characteristics of the supercharging system-load are obtained, and the constructed supercharging system-load transient matching point migration model is simulated to obtain the operation point migration law of the supercharging system-load under transient conditions; then, based on the energy flow characteristics of the supercharging system-load, the feasible operation domain of the supercharging system-load is reconstructed to obtain the steady-state operation domain of the supercharging system-load; and according to the operation point migration law under transient conditions, the feasible operation domain of the supercharging system-load is reconstructed to obtain the transient operation domain of the supercharging system-load. The application can accurately reconstruct the steady-state operation domain and the transient operation domain corresponding to the gas turbine driven supercharging system, and provide a decision basis for subsequent efficient operation and safe operation under full working conditions.

The invention relates to the technical field of MEMS (Micro Electro Mechanical System) control, and discloses a system and a method for controlling an MEMS (Micro Electro Mechanical System) micromirror array. The method comprises the following steps: establishing a space-time characteristic evaluation model containing an energy flow analysis domain and a mechanical response domain, synchronously acquiring feed-in and load energy waveform characteristics of a system, and obtaining stress distribution data of a driving mechanism and real-time attitude data of a reflecting surface of each micro-mirror in parallel; and the data are fused to generate a multi-dimensional feature vector, and the multi-dimensional feature vector is compared with a preset stability boundary condition, so that a targeted regulation and control strategy is output. According to the method, multi-dimensional state sensing from energy transfer efficiency to internal stress of a mechanical structure is realized, the hysteresis quality caused by the fact that a traditional method only depends on motion feedback is overcome, the performance degradation trend and potential mechanical damage can be recognized in advance, a control system is enabled to turn from passive error correction to active early warning and health management, and the reliability of the system is improved. And the working stability and adaptability of the micromirror array are improved, and the service life of the device is prolonged.

The application relates to the technical field of micro-electro-mechanical system control, and discloses a system and method for controlling a MEMS micromirror array. The method comprises the following steps: establishing a space-time characteristic evaluation model comprising an energy flow analysis domain and a mechanical response domain, synchronously collecting the input and load energy waveform characteristics of the system, and acquiring the stress distribution data of the driving mechanism and the real-time attitude data of the reflecting surface of each micromirror in parallel. The data are fused to generate a multi-dimensional feature vector, which is compared with preset stability boundary conditions, so that a targeted regulation strategy is output. The method realizes multi-dimensional state perception from energy transmission efficiency to internal stress of the mechanical structure, overcomes the hysteresis of the traditional method which only depends on motion feedback, can identify the performance degradation trend and potential mechanical damage in advance, makes the control system change from passive error correction to active early warning and health management, and improves the working stability, adaptability and service life of the micromirror array.

The present application relates to the technical field of comprehensive energy, and provides a safety evaluation method and system for comprehensive energy system planning based on energy path theory, a continuous flow model is constructed by combining a steady-state alternating current flow model of a power system and a dynamic gas flow model of a natural gas system, the limitations of traditional static models that cannot depict the dynamic differences of multi-energy systems are broken through, the system response characteristics under faults are more truly reflected, the linear sensitivity method of saddle node bifurcation point singularity is used to realize rapid preliminary screening of faults, the load margin is accurately estimated by combining generalized curve fitting to complete secondary screening, and the final fault set is accurately evaluated through dynamic continuous energy flow analysis, which not only solves the problems of existing partial optimism and insufficient dynamic response depiction, but also considers the influence of electric-gas faults in a unified framework, gradually identifies key vulnerable lines and load margin indicators, and significantly improves the accuracy and reliability of comprehensive energy system safety evaluation.