30 results about "Energy intensity" patented technology

The invention relates to an exception tool for a virtual security network system. A virtual security net system includes: at least one active remote sensor configured to output energy to establish an energy security net and to detect reflected energy reflected from an object disposed in the energy security net; and a processor in signal communication with the at least one active remote sensor. The processor is configured to determine an energy intensity of the reflected energy and, in response to the energy intensity exceeding an energy intensity threshold, identify the object as an exceptional tool allowed to be disposed in the energy security net.

Provided is an optical system of a laser processing device and a laser processing device in which the energy utilization efficiency of laser light is high and the energy intensity distribution of an irradiation point (spot) of laser light that is suitable for a processing target of various materials can be selected. To achieve this, the optical system of the laser processing device has an optical surface in which a plurality of different focal points are provided on an optical axis, the energy intensity distribution of laser light on a surface perpendicular to the optical axis differs depending on the position on the optical axis, and by using different positions on the optical axis as the irradiation point of laser light of a processed object, the energy intensity distribution of laser light at the irradiation point of laser light of the processed object can be selected.

The application relates to a power transmission line fault maintenance method and system under severe weather. The method comprises the following steps: performing baseline correction on a traveling wave current signal to identify a wave peak interval corresponding to the traveling wave, determining the symmetry deviation of the wave peak interval according to the difference between the trend item components of two sequences, screening a plurality of suspected fault traveling waves according to the fitting goodness of each wave peak interval, the shape similarity between the two sequences and the symmetry deviation, determining the spatial similarity according to the similarity between each suspected fault traveling wave and a plurality of suspected fault traveling waves at the opposite end, determining the incident waves at both ends of the power transmission line according to the energy intensity of the wave peak interval and the spatial similarity, correcting the initial speed of the incident wave according to the preset corresponding relationship and the main frequency of each incident wave, and positioning the fault point according to the corrected speed and the arrival time of the corresponding incident wave. The method improves the fault positioning accuracy and reliability, and reduces the operation and maintenance difficulty of the power transmission line.

A non-contact motion physiological sensing method and a motion physiological sensing radar. The non-contact motion physiological sensing method is executed by a processor in a signal processing device, comprising: obtaining a digital signal; obtaining a phase map and a vibration frequency map according to the digital signal, the phase map presenting an energy distribution varying with a distance relative to the motion physiological sensing radar and a phase variation, and the vibration frequency map presenting an energy distribution varying with a distance relative to the motion physiological sensing radar and a vibration frequency variation; selecting at least one candidate position with an energy intensity exceeding an energy threshold from the vibration frequency map; selecting a target position from the candidate positions; obtaining one or more target phase data according to the target position; and inputting the one or more target phase data into a machine learning model to obtain a physiological parameter prediction result. The non-contact motion physiological sensing method and the motion physiological sensing radar can accurately sense the physiological parameter in the motion state of the subject in a non-contact manner.

The invention discloses an intelligent monitoring system for a high-low voltage power line based on multi-modal data fusion, which relates to the technical field of power line monitoring and comprises a space unification module, a line energy calculation module, a conflict quantification module and a cross-modal fusion module. The problem that an expansion joint siphon drainage linear cold belt is a thermal defect of a cable body is easily misjudged in the prior art is solved. The space unification module unifies the same world coordinate system, calculates a geometric proximity right, and maps optical fiber temperature measurement into arc length temperature through linear interpolation; the linear energy calculation module calculates linear energy intensity through the median of the temperature values based on the infrared thermal image surface temperature field; the conflict quantification module sets a range interval according to the inherent spatial resolution of the optical fiber, calculates a local temperature fluctuation value, obtains a cross-modal conflict value through calculation, and quantifies a cross-modal response conflict; and the cross-mode fusion module normalizes the three parts, and takes the root of the cubic of the product to obtain a cross-mode comprehensive value, so that the defects of the cold belt and the body are accurately judged, and the monitoring intelligence and the operation and maintenance accuracy are improved.

The invention relates to the technical field of evaluation of carbon emission detection indexes, in particular to an evaluation mechanism method of carbon emission detection indexes, which comprises the following steps of: constructing a three-level index system, establishing three first-level indexes, setting 6 second-level indexes, and subdividing into 18 third-level indexes; index data monitoring: collecting enterprise three-level index original data, including target year setting, energy ratio, carbon emission, energy consumption intensity and other values; performing index score assignment through a comprehensive scoring method, a standardized score assignment method and a quantile score assignment method; calculating hierarchical scores; and calculating the total score of the enterprise. Three types of scoring methods are customized for index characteristics, MK trend inspection is embedded, the significant emission reduction trend is objectively recognized through the statistic Z value, the traditional static evaluation shackle is broken through, the transverse fairness and longitudinal comparability of the evaluation result are improved, enterprises are driven to actively optimize the emission reduction path through a dynamic scoring mechanism, and the evaluation efficiency is improved. And a reliable basis is provided for accurate policy regulation and control.

This invention relates to an energy management method, apparatus, and display screen for a display screen. The energy management method of this application is applied to a display control system. The method includes: analyzing and processing energy parameters acquired by an energy harvester to obtain an energy intensity curve representing intensity changes and stability; processing the energy intensity curve based on a preset energy assessment model to obtain collectable energy data and controlling the energy harvester to collect the energy; the display control system can process the power supply requirements of the display module and the energy conversion information fed back by the energy conversion memory to generate energy allocation instructions to control the energy conversion memory to rationally allocate the converted and stored energy. This method can convert renewable resources into electrical energy, achieving self-powering of the display screen, which is more energy-efficient and environmentally friendly, while also eliminating dependence on the power grid and expanding the application scenarios of the display screen.

A virtual elevator safety net configuration system includes an active remote sensor configured to output energy within field of view (FOV) and to detect the energy reflected from an object located in the FOV, and one or more markers arranged within the FOV to define a spatial region of interest. The one or more markers are configured to reflect the energy having a first energy intensity to the active remote sensor. The virtual elevator safety net configuration system further includes a processor in signal communication with the active remote sensor. The processor is configured to determine the spatial region of interest within the FOV based at least in part on the reflected energy having a first energy intensity.

A virtual safety net system includes at least one active remote sensor configured to output energy that establishes an energy safety net and to detect reflected energy that is reflected from an object disposed in the energy safety net, and a processor in signal communication with the at least one active remote sensor. The processor is configured to determine an energy intensity of the reflected energy and to identify the object as an exception tool permitted to be disposed in the energy safety net in response to the energy intensity exceeding an energy intensity threshold.

The invention discloses a multi-source energy supply backscattering video transmission system and method, and relates to the technical field of wireless communication of the Internet of Things. Comprising a video acquisition unit used for acquiring image data; the data compression unit is used for compressing the image data; the backscattering modulator unit is used for mapping the compressed image data into a modulation control instruction through a table look-up mapping coding mechanism and sending the modulation control instruction; the energy and control management unit is used for adjusting the transmission rate and the data packet structure of the modulation control instruction according to the intensity of the radio frequency signal; the determining unit is used for determining whether to continuously provide energy and energy types for the active unit according to the radio-frequency signal intensity and the sunlight energy intensity; and the processor is used for predicting an energy failure trend according to the historical radio frequency signal intensity data, and determining the energy size of the radio frequency signal energy provided for the active unit according to the energy failure trend. According to the invention, the video transmission efficiency of the backscattering video transmission system in a weak signal environment is improved.

1. The name of the design product: graphical user interface for visualizing the impact of green innovation capability on energy intensity for electronic devices. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the interface change state diagram. 4. The picture or photo that best indicates the design points: interface change state diagram. 5. The use of the graphical user interface: the graphical user interface is used to realize the visual display of the impact of green innovation capability on energy intensity. 6. The human-computer interaction mode of the graphical user interface: after entering the mobile phone number, password and verification code in the main view, click login to enter the interface change state diagram. 7. Other circumstances that need to be explained: in the interface change state diagram, the × part is a variable content picture and the * is a variable number.

The invention discloses a multi-path biased VSP interference earthquake method and device, electronic equipment and a medium. The method may include: sorting biased VSP data into a common geophone gather; aiming at the common detection point gather, setting the length and the collection frequency of the multi-path signal; and multi-path signals of the two observation points A and B are calculated, and then a virtual seismic source waveform, namely a multi-path interference record, is calculated. According to the invention, interference calculation is carried out by using a multi-path summation principle, the energy intensity of underground effective reflection can be improved, and the energy of a cross phase is weakened by using the instability of the cross term.

The application relates to a multi-sensor-based power transformer fault automatic early warning device and method. The device comprises a determination module, which determines power weight values corresponding to IMF components of each frequency band of the same type according to the energy change correlation between the IMF components of the same frequency band and the energy intensity of the IMF components of each frequency band for decomposed data of the same power type; an analysis module, which analyzes the amplitude fluctuation characteristics of each IMF component in the time domain and the power spectrum density distribution thereof in the frequency domain to obtain power filter values corresponding to each IMF component; a reconstruction module, which reconstructs multiple IMF components in each kind of decomposed data after filtering to obtain each kind of reconstruction data corresponding to each kind of decomposed data; and a warning module, which determines to issue a warning if the average of the differential values of the amplitudes of each kind of reconstruction data is greater than a corresponding preset threshold. The application solves the limitation problem of the traditional filtering method in a complex signal environment and improves the accuracy and reliability of fault warning.

The application discloses a high-risk hidden danger area detection method based on a ground penetrating radar, and relates to the technical field of wireless detection.The method comprises the following steps: obtaining radar detection data along a target dam body measuring line; calculating water content change data at different measuring points based on the energy intensity distribution of different measuring points in the radar detection data; calculating a displacement cost matrix based on the displacement degree between different time instants of a water content change tracer point corresponding to the water content change data at each measuring point; determining a cooperative displacement cost matrix of each measuring point based on the displacement difference between parallel paths formed by different element values in the displacement cost matrix; determining a seepage channelization index based on the displacement cost matrix and the cooperative displacement cost matrix; and performing risk division processing on the area where each measuring point is located based on the displacement cost matrix corresponding index and the seepage channelization index.The application achieves the technical effect of accurately detecting high-risk areas in a dam when hidden dangers occur early.

This application discloses a power supply method and apparatus for a refrigerant leak detection unit. The power supply method for the refrigerant leak detection unit includes: determining the power consumption of the refrigerant leak detection unit when an environmental energy harvesting unit supplies power to it; and adjusting the energy emission intensity of an energy emission unit based on the power consumption, so that the power generation obtained by the environmental energy harvesting unit based on the energy emitted by the energy emission unit is greater than or equal to the power consumption of the refrigerant leak detection unit in its current operating mode. Thus, regardless of whether the refrigeration equipment is powered off, as long as the energy emission unit can emit energy, the refrigerant leak detection unit can operate normally.

The invention relates to a virtual safety net configuration system, and specifically, a virtual elevator safety net configuration system includes an active remote sensor configured to output energy within a field of view (FOV) and to detect energy reflected from an object located in the FOV; and one or more indicia disposed within the FOV to define a spatial region of interest. The one or more indicia are configured to reflect energy having a first energy intensity to the active remote sensor. The virtual elevator safety net configuration system also includes a processor in signal communication with the active remote sensor. The processor is configured to determine a spatial region of interest within the FOV based at least in part on the reflected energy having the first energy intensity.

This invention provides a method and system for detecting the density of concrete structures within bridges, relating to the field of concrete density detection technology. By differentially processing the echo signal, this invention effectively suppresses background noise in concrete box girders; furthermore, by performing modal decomposition to identify and eliminate high-frequency noise, it significantly reduces interference from the reinforcing steel frame, achieving signal purification. Moreover, by employing an identification method combining energy intensity and phase characteristics, it reduces the impact of signal attenuation on the evaluation results, enabling the differentiation and identification of echo signals from deep dense areas and shallow defect areas, which are easily confused in terms of energy performance. This distinguishes between corrugated pipes and voids, enhancing the overall detection accuracy of the system and its ability to combat false alarms and missed alarms.

The invention discloses a driving factor analysis and effect verification method for industrial waste gas emission space unevenness. The method comprises the following steps: acquiring industrial waste gas emission, industrial energy consumption, total energy consumption, total domestic production value and population data of a plurality of sub-regions in a target region; calculating a total industrial waste gas emission Tele index of the target area, and decomposing the index into intra-group uneven components and inter-group uneven components; the per capita industrial waste gas emission of the sub-regions is decomposed into a product of a pollution intensity effect factor, an industrial structure effect factor, an energy intensity effect factor and an economic development effect factor; variable coefficients of differences of the four driving factors among the sub-regions in the target region are calculated respectively and serve as agent variables; establishing a metering economy model, and performing regression analysis by taking a Tele index as a dependent variable and an agent variable as an independent variable; and analyzing marginal effect coefficients of independent variables on different quantiles by adopting a multivariate quantile-quantile regression model.

The invention relates to the technical field of smart cities and green buildings, in particular to a residential area energy-carbon effect real-time prediction method based on multiple evaluation indexes. The method comprises the following steps: S1, collecting multi-source data, cleaning the collected data, and constructing a residential district hierarchy basic database with a spatial topological relation; s2, based on the basic database, calculating a multivariate evaluation index system including an energy intensity index, a carbon emission intensity index, an environment thermal comfort index and an economic feasibility index; s3, constructing an energy carbon effect real-time prediction model; and S4, receiving the real-time data flow of the residential district Internet of Things through the energy-carbon effect real-time prediction model. According to the residential area energy-carbon effect real-time prediction method based on the multivariate evaluation indexes, accurate diagnosis, dynamic prediction and strategy intelligent matching of the existing residential area energy-carbon effect are realized by constructing a full-cycle working process of data acquisition and cleaning, the multivariate evaluation indexes, the prediction model and visual suggestion.

This invention relates to the field of data measurement technology, specifically to an intelligent data acquisition and processing method for gate flowmeters. The method involves: obtaining the main period duration based on the spectral distribution characteristics of the component signals of the flow velocity time series; obtaining sliding windows at different positions in the component signals based on the main period duration; obtaining continuous data characteristic values ​​based on the differences in data change trends between adjacent sliding windows; obtaining overall stable characteristic values ​​based on the differences in data change trends between different sliding windows; obtaining the component comprehensive reliability based on the continuous data characteristic values ​​and the overall stable characteristic values; obtaining a reliability coefficient based on the differences in component comprehensive reliability and the differences in the main period duration; and obtaining the energy intensity based on the amplitude characteristics of the component signals. This invention obtains the importance level based on the reliability coefficient and energy intensity; and obtains the fused flow velocity time series based on the component signals and their corresponding importance levels, thereby improving the accuracy of flow measurement.

This invention relates to a multi-variable collaborative energy intensity optimization method for fluidized bed desulfurization processes, and to the field of fluidized bed desulfurization process optimization. This invention defines a comprehensive desulfurization energy intensity index that uniformly converts the heat penalty, electricity consumption, and limestone embodied energy in the desulfurization process into standard energy consumption; establishes a fluidized bed desulfurization process model coupling microscopic reaction kinetics and macroscopic fluid dynamics, and uses its output data combined with actual operating data to train the energy consumption model; with the goal of minimizing comprehensive desulfurization energy intensity and with emission compliance and safe operation as constraints, a multi-objective collaborative optimization model is established, and a multi-objective optimization algorithm is used to collaboratively optimize bed temperature, calcium-sulfur ratio, primary air rate, and limestone particle size to obtain the optimal combination of operating parameters. This invention can optimize the energy utilization efficiency of the desulfurization process, significantly reduce the comprehensive energy consumption of the fluidized bed system while ensuring emission compliance, and has significant economic and social benefits.

The invention discloses an industrial park carbon peak-reaching deduction method, which comprises the following steps: constructing an STIRPAT model to deduce an industrial park carbon peak-reaching result based on the population scale, per capita GDP, energy intensity, energy consumption structure, industrial structure and carbon emission data of an industrial park; based on the energy structure data of each field of the industrial park, constructing an LEAP model to deduce a carbon peak reaching result of the industrial park; based on the historical carbon emission time sequence of the industrial park, constructing an ARIMA model to deduce a carbon peak reaching result of the industrial park; and analyzing the carbon peak reaching results of the industrial park deduced by the STIRPAT model, the LEAP model and the ARIMA model by using a reciprocal method of variance to obtain the final carbon peak reaching time and carbon emission of the industrial park. According to the method, the credible accuracy of industrial park carbon reaching peak deduction is improved.

The invention relates to a power transformer fault automatic early warning device and early warning method based on multiple sensors. The device comprises a determination module for determining the power weight value corresponding to the IMF component of each frequency band of the same type according to the energy change correlation degree between the IMF components of the same frequency band and the energy intensity of the IMF component of each frequency band for decomposition data of the same electric quantity type; the analysis module is used for analyzing the amplitude fluctuation characteristic of each IMF component in the time domain and the power spectrum density distribution of each IMF component in the frequency domain to obtain a power filtering value corresponding to each IMF component; the reconstruction module is used for reconstructing a plurality of IMF components in each kind of decomposed data after filtering to obtain each kind of reconstructed data corresponding to each kind of decomposed data; and the early warning module is used for determining to send out early warning if the mean value of the difference values of the amplitudes of the reconstructed data is greater than a corresponding preset threshold value. The problem of limitation of a traditional filtering method in a complex signal environment is solved, and the accuracy and reliability of fault early warning are improved.

The application discloses a high-risk hidden danger area detection method based on a ground penetrating radar, and relates to the technical field of wireless detection.The method comprises the following steps: obtaining radar detection data along a target dam body measuring line; calculating water content change data at different measuring points based on the energy intensity distribution of different measuring points in the radar detection data; calculating a displacement cost matrix based on the displacement degree between different time instants of a water content change tracer point corresponding to the water content change data at each measuring point; determining a cooperative displacement cost matrix of each measuring point based on the displacement difference between parallel paths formed by different element values in the displacement cost matrix; determining a seepage channelization index based on the displacement cost matrix and the cooperative displacement cost matrix; and performing risk division processing on the area where each measuring point is located based on the displacement cost matrix corresponding index and the seepage channelization index.The application achieves the technical effect of accurately detecting high-risk areas in a dam when hidden dangers occur early.

This invention relates to the field of online monitoring and fault identification technology for transformers and reactors, specifically a method for identifying gas faults in transformer oil based on data discretization and normalization. The method includes the following steps: obtaining characteristic quantities of dissolved gases in transformer oil; calculating normalized energy intensity using these characteristic quantities; performing fuzzy discretization and normalization on the characteristic quantities and normalized energy intensity to obtain characteristic parameter one; standardizing the ratios of different dissolved gas characteristic quantities using the three-ratio method to obtain characteristic parameter two; and constructing a fault diagnosis model based on characteristic parameters one and two to identify gas fault types. This method improves the speed, accuracy, and precision of transformer fault detection, enabling accurate judgment of transformer faults. Applying it to transformer monitoring systems can more effectively detect early latent faults in transformers, increasing the value of the monitoring system, reducing on-site maintenance work and costs, and improving the safety of maintenance work.

The invention discloses a blade connection state evaluation method and device and a readable storage medium, and the method comprises the steps: periodically and synchronously collecting multiple acoustic signals of multiple blades, so as to extract multiple denoising signals corresponding to the multiple acoustic signals, and each acoustic signal corresponds to one blade; impact components in the de-noised signals are extracted, impact energy factors corresponding to the de-noised signals are calculated, and the impact energy factors represent the energy intensity of the impact components; and for any path of target de-noised signal in the paths of de-noised signals, calculating an abnormal value proportion of an impact energy factor corresponding to the target de-noised signal, and evaluating a connection state of a blade corresponding to the target de-noised signal based on the abnormal value proportion. According to the technical scheme provided by the invention, the blade connection state can be monitored at relatively low cost.

The utility model discloses an energy cell repairing instrument convenient to operate and use, which belongs to the technical field of health equipment, solves the defects of the existing cell repairing instrument in the aspects of operation and use, such as complicated operation, difficulty in mastering and inconvenience brought to users, and comprises a main body, an operation panel is arranged at the top end of the main body, and a power supply is arranged on the operation panel. A wiring port is formed in the operation panel, the wiring port is connected with a patch making contact with a human body through a wire harness, the overall operation is simple, the overall operation can be operated through the operation panel, treatment parameters such as energy intensity and treatment time can be adjusted according to requirements, and in addition, when the device is used, the device is convenient to use, and the device is convenient to use. The wiring harnesses can be distributed in order, the attractiveness is guaranteed, workers can be prevented from being stumbled, and the use requirements of people are met.

The invention provides a multi-vehicle homogeneous cooperative behavior decision-making method and device. The method comprises the following steps: acquiring information and environment perception information of a plurality of vehicles in a target area; the vehicles comprise controllable vehicles and uncontrollable vehicles; determining the energy intensity distribution of a front area of any target controllable vehicle based on the information of the multiple vehicles in the target area; determining a first feasible region of any target controllable vehicle based on the environmental perception information and the energy intensity distribution of the region in front of any target controllable vehicle; determining a second feasible region of any target controllable vehicle based on the excitation value of the first feasible region of any target controllable vehicle; and according to a preset cooperation strategy, the second feasible region of the controllable vehicle with the conflict is eliminated. According to the invention, homogeneous, generalized, efficient and safe cooperative behavior decision of multiple vehicles in a complex road scene can be realized.

This invention relates to the field of power load forecasting technology, and in particular to a method for optimizing power equipment resource allocation based on intelligent analysis. This method converts historical load data sequences of a power system to the frequency domain to obtain a frequency richness assessment value. Based on the frequency richness assessment value, it obtains the adaptive component number of the VMD algorithm and decomposes the historical load data sequence into multiple component signals. Based on the load acquisition value and load forecast value of data points within the prediction analysis interval of any component signal, it performs prediction error analysis on any component signal at different preset quantiles to obtain an overall error value. Based on the energy intensity within the prediction analysis interval, it obtains the prediction influence weight of any component signal. It obtains the load forecast value corresponding to each component signal and combines the overall error value and prediction influence weight of each component signal to obtain a load forecast value interval, which is used for power equipment resource allocation optimization, significantly improving the accuracy and stability of load forecasting.

The invention relates to the technical field of carbon emission prediction and energy policy analysis. According to the STIRPAT model scene analysis-based carbon emission total amount and carbon peak time prediction method, scenes under different energy policy influences are generated, an established STIRPAT model is combined to predict the carbon emission total amount and the carbon peak time, influence factors related to the energy industry, such as the population scale, the regional total production value, the energy consumption and the energy intensity, are focused on, and the prediction accuracy is improved. Development scenes under the influence of different energy policies are obtained, the scenes are substituted into the model to obtain the predicted total carbon emission amount and carbon peak reaching time, energy policy suggestions are given, effective reference is provided for formulating reasonable energy policies meeting requirements, and dual-carbon target implementation is promoted.