147 results about "Energy parameter" patented technology

The invention relates to the technical field of fault detection, in particular to an intelligent sensing online monitoring system and method for a ring main unit, and the system comprises an energy collection module, a sudden change analysis module, an abnormity locking module, a risk partitioning module and a link synchronization module. According to the method, an energy parameter is formed through 50 millisecond sampling period integration, a short-time energy change characteristic is captured, an abnormal segment is extracted based on a sudden change rate threshold value, an energy change direction and sudden change amplitude are extracted to lock an abnormal starting point, a leakage current instantaneous value is continuously collected, and a maximum amplitude and an average amplitude are extracted to calculate offset quantification insulation fluctuation. And calling time window data to calculate an amplitude fluctuation rate, executing multi-threshold judgment and evaluation of a degradation degree, packaging an energy parameter, an amplitude offset and insulation grade information in combination with an offset, executing synchronization consistency to correct node deviation, ensuring reliable data synchronization, and improving insulation trend identification sensitivity and abnormal state monitoring accuracy.

The invention discloses an energy acquisition and monitoring system based on big data, particularly relates to the field of energy monitoring, is used for solving the problem of energy consumption abnormity identification and management optimization in steel production, and is characterized in that energy parameters are acquired in a production process, and an energy signature reference model of multi-dimensional energy consumption characteristics is constructed based on historical data and equipment operation characteristics; an accurate reference is provided for dynamic comparison and anomaly detection; potential anomalies are accurately identified by utilizing comprehensive analysis of energy consumption deviation distribution and load characteristics, and key influence factors and root causes are deeply mined through a multivariable machine learning algorithm; in combination with a predictive scheduling engine and an online optimization algorithm, process parameters, equipment running states and task schedules are dynamically adjusted, abnormities are effectively eliminated, and energy consumption balance is recovered; therefore, the real-time monitoring and intelligent anomaly detection of the process energy consumption are realized, the refinement level of energy management is improved, the energy utilization efficiency and production stability of iron and steel enterprises are improved, and the potential production risk is reduced at the same time.

The invention discloses a switch cabinet discharge detection method and system, and relates to the technical field of power equipment state monitoring and fault diagnose.The light intensity attenuation rate and the vibration frequency are collected through a photonic crystal fiber, the concentration of decomposed gas is detected in combination with a Raman spectrum, and a space-time joint feature matrix is generated; performing space weight distribution on the space-time joint feature matrix based on the switch cabinet structure, and inputting the space weight to an RBF-SVM (Radial Basis Function-Support Vector Machine) to generate discharge type probability distribution; based on a high-frequency energy parameter and a gas decomposition concentration parameter in the spatio-temporal joint characteristic matrix, inputting the parameters into a multiple linear regression model, calculating an insulation aging index, and judging an insulation degradation grade according to a threshold value; the photonic crystal fiber is used for collecting the light intensity attenuation rate and the vibration frequency, the Raman spectrum is combined for detecting the decomposition gas concentration to generate the space-time joint characteristic matrix, synchronous monitoring of various physical and chemical parameters in the switch cabinet is achieved, and the accuracy and comprehensiveness of recognition of different types of discharge phenomena are improved.

The invention relates to the field of theoretical calculation and numerical simulation of ship structure protection and cavitation, in particular to a bubble pulsation initial condition inversion method and system based on a bubble energy loss target. Inputting characteristic parameters and energy parameters of the bubbles, and determining a target variable value of inversion calculation; taking a bubble maximum volume moment as an initial calculation moment, randomly giving a bubble internal pressure value at the bubble maximum volume moment, and determining a bubble initial condition in inversion calculation; reversely carrying out time integration on the basis of a compressible spherical bubble pulsation equation to obtain bubble characteristic parameters at zero moment; calculating a time calendar evolution process of a bubble radius by taking a bubble characteristic parameter obtained by reverse time integration as a bubble pulsation initial condition, and judging whether the energy loss of the bubble reaches a target value or not; and adjusting the bubble internal pressure value at the moment of the maximum volume of the bubbles for re-calculation, solving a bubble radius time calendar process, and recording bubble characteristic parameters after reaching an expected target as a new bubble pulsation initial condition. The method is used for solving the problem that the initial bubble pulsation condition is difficult to determine in the existing bubble dynamics theory and numerical calculation.

The invention relates to the technical field of seismic source analysis and inversion, and discloses a seismic source analysis and inversion system based on mine earthquake monitoring, which is characterized in that energy parameters are generated through waveform feature extraction, mine earthquake event identification and accurate positioning are realized by using a space-time aggregation rule, and seismic source mechanism parameters are inverted in combination with a seismic wave initial motion parameter and amplitude relationship. On the basis, a regional stress field initial inversion model is constructed, a stress gradient is calculated in combination with a working face track and stratum information, a principal stress rotation composite index is determined through interlayer mechanical difference and a spatial change rate, and self-adaptive deformable partitions are generated. And finally, secondary stress field inversion is carried out in the subareas, the corrected maximum principal stress direction is output, high-precision dynamic analysis of a mine earthquake mechanism and stress distribution is realized, and the mine disaster prediction and early warning capability is remarkably improved.

The invention discloses a welding seam detection and self-adaptive welding gun energy adjusting system and method, and relates to the technical field of welding control. The system comprises an image acquisition module, an image data processing module, a machine learning model, an energy detection module, a welding gun control module and a display interface, wherein the image acquisition module is responsible for acquiring a welding seam image in a welding process; the data processing module preprocesses the acquired image, such as de-noising and filtering; the machine learning model adopts a neural network to perform feature extraction and classification on the weld seam image; the welding gun control module adjusts energy output of a welding gun in real time according to an output result of the machine learning model; the display interface displays the welding seam detection result and the welding gun energy adjusting condition in real time. According to the system and the method, the welding seam defect can be automatically identified by analyzing the welding seam characteristic data in real time so as to improve the welding seam detection accuracy and efficiency, and the energy parameters of the welding gun are dynamically adjusted according to the detection result, so that the welding quality and efficiency are improved.

The invention relates to the technical field of energy data management and control, and discloses a smart park energy data dynamic management and control system. The energy data acquisition module of the system acquires and preprocesses the operation data flow in the park in real time. The energy feature analysis module performs multi-dimensional feature extraction on the data stream, and identifies feature vectors such as peak load and steady-state operation. The event trigger engine generates an energy management event signal based on conditions such as feature vector and threshold comparison, timing pattern matching and the like. The parameter node identification module analyzes an event signal time sequence and positions key nodes such as equipment start and stop and load sudden change. The offset calculation module calculates the offset of the energy parameter relative to the historical reference for the key node. The similar parameter derivation module derives a migratable parameter set containing general control parameters and scene adaptive parameters according to the offset and a historical database. And the dynamic regulation and control module performs real-time adjustment such as power distribution and equipment scheduling on park energy distribution by using the set.

The invention provides a method and a device for determining hyper-parameters of a potential energy model based on a graph neural network. The method comprises the following steps: acquiring a key sample from a plurality of samples of a data set for molecular dynamics simulation; determining a truncation radius configuration of the potential energy model based on the key sample, the truncation radius configuration including a truncation radius of each element combination; training of the potential energy model is performed based on the key sample and the truncation radius configuration, and the truncation radius configuration is adjusted based on an inference result of the trained potential energy model, where an input of the potential energy model is an atomic graph determined based on the key sample and the truncation radius configuration, and an output of the potential energy model is an atomic graph determined based on the key sample and the truncation radius configuration. The output of the potential energy model comprises energy parameters and force parameters of atoms.

The invention discloses a rock triaxial statistical damage constitutive model construction method based on an energy dissipation theory. The method comprises the following steps: step 1, defining a function relationship between an energy dissipation ratio and an axial strain corresponding to a rock test piece; 2, obtaining a rock damage evolution equation; 3, constructing a rock damage constitutive model; and 4, obtaining stress-axial and radial strain relation curves of the rock through an indoor test, determining mechanical strength parameters and energy parameters of the rock sample according to test data, identifying model parameters according to a test result, and determining a damage threshold value according to an energy dissipation ratio-axial strain relation curve stagnation point. According to the rock triaxial statistical damage constitutive model construction method based on the energy dissipation theory provided by the invention, the problem in the prior art that the rock damage evolution process cannot be represented for a rock material showing obvious nonlinear characteristics in a compaction stage and a residual deformation stage is solved.

A control method and an aerosol generating device. The control method (S100) comprises: when receiving a heating starting instruction, on the basis of mapping relationships between time periods and energy parameters, respectively controlling, within a plurality of time periods, a power supply to provide corresponding energy for an induction coil, wherein the energy provided in each time period is composed of a plurality of high-frequency drive pulses, and the duration of the time period is greater than or equal to 500 ms (S10). Compared with conventional control modes depending on the real-time temperature of a heater and a temperature curve, the present control mode involves control of energy supply in different time periods; thus, the taste and vaping experience can be improved, dependence on temperature measurement devices can be eliminated, and hardware costs can be effectively reduced.

The invention discloses a smart energy management system based on low-altitude facilities and a method thereof. The system comprises a smart energy management middle platform, a data acquisition module, an energy consumption calculation module, an energy storage calculation module, a distribution strategy generation module and a management scheduling module. The data acquisition module is used for acquiring multi-source data of the low-altitude facility; the energy consumption calculation module is used for predicting the total loss power consumption of the low-altitude facility based on the real-time demand load and the information carried in the task instruction request; the energy storage calculation module is used for predicting the current energy storage capacity of the low-altitude facility based on the environment data and the energy parameter data; the distribution strategy generation module is used for obtaining a distribution strategy result; and the management scheduling module is used for updating energy supply and equipment operation parameters of the low-altitude facilities based on the distribution strategy result. According to the method, the distribution strategy result of energy management can be obtained from multiple dimensions, and the problems that the accuracy of energy management distribution is poor, and excessive waste of energy or equipment damage of low-altitude facilities is easily caused are solved.

The invention relates to the technical field of laser measurement, in particular to a laser spot energy distribution measurement method, device and equipment and a storage medium, and the method comprises the steps: firstly obtaining a to-be-simulated laser beam, calling a pre-trained laser light path transmission model to carry out the beam propagation behavior simulation of the to-be-simulated laser beam, and obtaining a simulation spot energy distribution parameter; constructing an initial light beam energy distribution model based on the simulation light spot energy distribution parameters, then optimizing model parameters of the initial light beam energy distribution model by adopting a beetle beetle algorithm to obtain a target light beam energy distribution model, and then obtaining real-time laser light spot energy parameters; inputting the real-time laser spot energy parameters into the target light beam energy distribution model for fitting calculation to obtain real-time spot energy distribution parameters, and finally performing visualization processing on the simulation spot energy distribution parameters and the real-time spot energy distribution parameters to obtain visualization data. The invention aims to realize high-precision and real-time reconstruction of the actual light spot form of the micro laser.

The invention discloses a coagulation and bipolar coagulation integrated control system for a surgical operating instrument, and relates to the field of medical equipment. The system comprises an interface module, an energy detection module, a storage module, a load model matching module and an energy output control module. According to the system, an energy detection signal is output to a surgical instrument before energy output, and a real-time biological impedance spectrum of a target object is obtained; determining a target model from pre-stored electrical load models according to the impedance spectrum, and calling a corresponding adaptive energy output strategy; and in the energy output process, the impedance change of the target object is monitored, and the energy parameters are dynamically adjusted, so that the energy output is automatically stopped after the impedance change conforms to the preset stable target state. The self-adaptive precise energy control based on the real-time state of the tissue is realized, the problems of tissue carbonization, adhesion or incomplete coagulation and the like are effectively avoided, and the operation safety and effect are improved.

Devices, systems, methods, and processes for energy scoring of network paths are described herein. Various network paths, each including one or more hops, may be identified in a network. Presence of additional hops in each network path may be determined. From the identified and determined hops, a set of hops may be determined for energy score determination. For each selected hop, a set of energy parameters may be determined and one or more weights may be assigned to the determined set of energy parameters. A weight may correspond to a level of confidence in or an accuracy of the energy parameter determination. An energy score of each network path may be determined based on the determined set of energy parameters and the assigned one or more weights. One network path may be selected based on the energy scores and traffic may be routed along the selected network path.

Optimized backscatter energy harvesting using a Reconfigurable Intelligent Surface (RIS) may be provided. Energy parameters may be received from a backscatter communication device. Then an energy critical message may be received from the backscatter communication device. The backscatter communication device may then be instructed to send frequent messages in response to receiving the energy critical message from the backscatter communication device. Next, a configuration for a Reconfigurable Intelligent Surface (RIS) cluster may be determined to supply energy to the backscatter communication device based on the energy parameters and the frequent messages. The RIS may be caused to supply energy to the backscatter communication device based on the configuration.

The invention relates to an RPV material small-size sample fracture toughness conversion evaluation method, which comprises the related steps of material fracture toughness testing based on energy method parameters, obtaining of crack initiation driving force energy parameters in a nuclear power structure integrity service state, and nuclear power structure service safety evaluation. The method provided by the invention overcomes the problems that the evaluation of the surface shallow crack is too conservative (the constraint effect of the crack front edge is not considered) and the SIF, J integral and other numerical simulation methods cannot be applied to the unloading process in the existing specification, and can be suitable for the load unloading characteristics of the primary loop of the reactor; and the deep technical support is provided for the long-life safe operation of the RPV of the nuclear power plant.

The invention relates to the technical field of laser processing, in particular to a PCB laser drilling path control method and system. The method comprises the steps of receiving hole geometric data; based on geometric data of the hole, identifying a sharp concave angle in the contour of the hole, and calculating the geometric shape and volume of a residual material area left due to the defect generated by the conventional path; a main filling path of the hole main body area is generated based on the hole geometric data, a supplementary cleaning path is generated for the residual material area, and the supplementary cleaning path and the main filling path are spatially separated from each other; matching laser energy parameters for the supplementary cleaning path based on material characteristics and volume of the residual material region; in the machining process, matched laser machining parameters are applied in stages corresponding to the main filling path and the supplementary cleaning path respectively. The problem of carbonization layering caused by material residues and excessive energy injection in laser drilling with sharp inner concave angles can be effectively solved, and the machining quality and the product reliability are ensured.

The invention discloses a laser processing alloy mesh material temperature field simulation method. The method comprises the following steps that a nickel-based alloy mesh material three-dimensional model conforming to the actual size is established; carrying out mesh division on the entity domain to obtain a mesh division model of the nickel-based alloy mesh material; setting physical attribute parameters; after pulse laser energy parameters are calculated, laser processing parameters are set, solid heat transfer related parameters are set, and laser source position parameters are set; and laser processing parameters are adjusted, and the temperature change of the surface of the nickel-based alloy mesh material and the trend and direction of heat conduction are analyzed. According to the temperature field simulation method for laser processing of the alloy mesh material, anisotropy of thermophysical parameters such as the heat conductivity coefficient of the nickel-based alloy mesh material is considered in the model, and the established model structure is closer to a woven structure of an actual sample piece and can be compared with an experiment more visually; and researchers can be helped to further grasp the characteristic change rule of the laser processing nickel-based alloy mesh material.

The application relates to a diffusion parameter determination method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: obtaining a first energy parameter of a target fuel cell under an oxygen vacancy structure and second energy parameters of the target fuel cell under a plurality of oxygen vacancy structures; processing the first energy parameter and each second energy parameter to obtain a free energy parameter corresponding to each oxygen vacancy structure; determining a target oxygen vacancy concentration according to the free energy parameter corresponding to each oxygen vacancy structure; constructing a structure model according to the target oxygen vacancy concentration, and solving the structure model through an ab initio molecular dynamics (AIMD) algorithm to obtain a target diffusion parameter corresponding to the target oxygen vacancy concentration; each oxygen vacancy structure refers to a structure corresponding to different oxygen vacancy concentrations in the target fuel cell. The method can improve the accuracy of the determined diffusion coefficient.

The present disclosure relates to a voice detection method, device, earphones and storage medium. The voice detection method includes: obtaining a first voice signal and a second voice signal, wherein the first voice signal is a sound signal obtained from the wearer's ear canal, and the second voice signal is a sound signal obtained from the wearer's environment; obtaining a first energy parameter and a second energy parameter, the first energy parameter represents the energy value of the first voice signal in a preset frequency band, and the second energy parameter represents the energy value of the second voice signal in a preset frequency band, wherein the preset frequency band is the frequency interval generated by the occlusion effect; obtaining a numerical relationship between the first energy parameter and the second energy parameter, and if the numerical relationship represents that the first energy parameter is greater than the second energy parameter, it is determined that the wearer has emitted a sound signal. Using the method in the present disclosure, it is possible to accurately determine whether the wearer of the earphones has emitted a sound signal without the need for additional sensor hardware and a microphone array composed of earphones.

A method for obtaining the reduction ratio of a continuous rolling mill unit that can reduce roll wear, including: inputting process parameters and continuous rolling mill equipment parameters; establishing an optimization objective and constraint conditions for the minimum roll gap friction work; initially setting the reduction ratio of each stand using an optimization algorithm; calculating the entrance thickness and exit thickness of the rolled piece for each stand; calculating the rolling force and energy parameters of each stand, where the rolling force and energy parameters of each stand include the rolling pressure, transmission torque, forward slip value, roll speed, and main motor power of each stand; determining whether the optimization objective and constraint conditions for the minimum roll gap friction work are simultaneously satisfied. The present invention can be used for online preset calculation of the reduction ratio distribution of a continuous rolling mill unit. The calculated reduction ratio distribution can minimize the roll gap friction work of the continuous rolling mill unit, thereby minimizing the total roll wear of each stand, reducing roll consumption during the rolling production process, lowering the roll change frequency, and increasing the rolling production volume during a single roll period.

This invention discloses a method for calculating needle-free injection depth based on energy analysis, comprising the following steps: Step 1, obtaining the jet process parameters during a single needle-free injection, and calculating the initial peak jet power and the total jet energy of this injection; Step 2, calculating the initial injection depth based on the initial peak jet power using a preset initial depth linear model; Step 3, calculating the diffusion depth increment based on the total jet energy using a preset diffusion depth linear model; Step 4, calculating the predicted maximum injection depth based on the sum of the initial injection depth and the diffusion depth increment. This invention decomposes the injection process into two stages: initial impact and subsequent diffusion, and establishes linear prediction models for each stage based on the jet energy parameters, thereby achieving reliable and accurate calculation and prediction of the injection depth for large-volume needle-free injections.

The provided method includes: determining an energy parameter and a co-volume parameter of a pure gas by a PR state equation, and determining a material parameter and a co-volume parameter of a mixed gas by a Waals one-fluid mixing rule and a combination rule; determining a Helmholtz free energy density and an equilibrium density of the pure gas by a Wertheim molecular association theory, and determining Helmholtz free energy and an equilibrium density of a (H2+N2) mixed gas with different components by a density mixing rule; determining an influence parameter of the pure gas by a gradient theory (GT), and determining an influence parameter of the mixed gas by the influence parameter of the pure gas and an interaction coefficient; simplifying a GT model; and obtaining the surface tension of the (H2+N2) / H2O system at different temperatures by combining the LGT model and the PR state equation.

Optimized backscatter energy harvesting using a Reconfigurable Intelligent Surface (RIS) may be provided. Energy parameters may be received from a backscatter communication device. Then an energy critical message may be received from the backscatter communication device. The backscatter communication device may then be instructed to send frequent messages in response to receiving the energy critical message from the backscatter communication device. Next, a configuration for a Reconfigurable Intelligent Surface (RIS) cluster may be determined to supply energy to the backscatter communication device based on the energy parameters and the frequent messages. The RIS may be caused to supply energy to the backscatter communication device based on the configuration.

An object of the present disclosure is to select an arrangement condition and an operation condition that ensure both comfort and energy conservation. The selecting step includes obtaining a plurality of device parameters satisfying both a first condition and a second condition based on a plurality of sets, each set including an air conditioning energy parameter and a comfort parameter that have been obtained for a plurality of samples, respectively. The first condition is a condition that the comfort parameter is a value greater than a threshold. The second condition is the condition that the air conditioner energy parameter is minimized within the range of the multiple equipment parameters meeting the first condition.

The present application provides a kind of open-air blasting hole net parameter determination method, device, electronic equipment and detection system, belongs to blasting engineering technical field.The method comprises: S1, obtains the rock mass explosibility parameter of target blast area, initial hole net parameter;S2, the parameters obtained and blasting energy parameters are input into numerical simulation model, and output prediction result;S3, obtains the measured result according to the current hole net parameter execution blasting;S4, according to the measured result and prediction result, corrects the parameters of numerical simulation model;S5, optimizes hole net parameter;S6, based on the iteration control of multi-objective optimization repeatedly executes S2-S5, and the first preset number of iterations control executes S2-S5, subsequent iteration control only executes S2 and S5;Until the prediction boulder rate exceeds the first threshold value, stop iteration, and the optimal hole net parameter with the prediction boulder rate less than the first threshold value is determined as target hole net parameter.The method is used to solve the problem of high explosive specific consumption in related art.

The invention discloses a comprehensive energy cooperative control method and device and a medium, and the method comprises the steps: carrying out the semantic mapping of a preset comprehensive energy association relationship in a node-edge manner, constructing an energy field ontology library, converting the comprehensive energy parameter data of an edge side into JSON data through a protocol conversion device deployed at the edge side, and carrying out the JSON data, the method comprises the steps of obtaining JSON data, performing semantic annotation on the JSON data according to a preset metadata tag system to generate a unified data stream, performing data cleaning on the unified data stream according to an energy field ontology library to generate a standardized data stream, and finally storing the standardized data stream to a preset multi-modal data lake according to a preset storage rule. And obtaining comprehensive energy scheduling data according to the standardized data flow in the multi-modal data lake. Through a multi-source heterogeneous data fusion mechanism, the data islanding phenomenon in the prior art is solved, and the overall response speed of the integrated energy system is improved by processing numerous multi-source heterogeneous data through Kafka + Flink.

The invention relates to a computer-implemented method for assessing the feasibility of applications (A) on a control unit (4) of an agricultural vehicle (1) supplied with energy by an electrical energy storage device (5), the method comprising a determination (100) of a first energy parameter (P1) based on an energy value (EA) required to carry out an application (A), and of a second energy parameter (P2) based on an energy value (EB) that can be provided by the energy storage (5), a comparison (110) of the first (P1) and the second (P2) energy parameter, and a prevention (120) or permission (130) of the execution of the application (A) depending on the comparison (110).

This application discloses a cutting system and method for orthodontic appliances. The cutting method includes: obtaining a tooth model, wherein the tooth model is based on a tooth model obtained before, during, or after orthodontic treatment; obtaining thickness information of the orthodontic appliance in the region where at least one tooth is located based on the tooth model; segmenting the orthodontic appliance based on the thickness information to obtain multiple segment intervals; determining a first energy parameter based on the segment intervals, wherein the first energy parameter is used to characterize the relationship between the energy of the laser and the thickness to be cut; and cutting the area to be cut of the orthodontic appliance corresponding to the segment intervals based on the first energy parameter. This cutting method allows the laser energy to be adapted to the cutting requirements of different cutting thicknesses, which is beneficial to achieving precise energy control during the orthodontic appliance cutting process. Therefore, this cutting method has better dynamic performance and a higher cutting adaptation rate for orthodontic appliances with complex curved surfaces.