49 results about "Load measurement" patented technology

The invention relates to the technical field of multi-core CPU task scheduling, and discloses a multi-core CPU task scheduling optimization method based on load balancing. The method comprises the following steps: continuously monitoring an output value of a load balancing indicator in a multi-core CPU task scheduler, and setting a current task distribution mode as reference task distribution when a system is balanced; collecting an instant load measurement value of each processing core, constructing a load distribution sequence, calculating a load deviation parameter distributed with a reference task, and determining a load imbalance degree and a skew core identifier; based on the state updating indicator output value, generating a task redistribution instruction to adjust the task distribution direction; and during task execution, task operation data associated with the unique identifier is collected in real time, and performance is evaluated and stored after segmentation processing according to categories. According to the method, accurate sensing and dynamic adjustment of the load state are realized, the task allocation logic is optimized, and the scheduling rationality and operation efficiency of the multi-core CPU are improved.

The invention discloses a self-adaptive heuristic grid clustering method suitable for non-intrusive load monitoring, which comprises the following steps of: S1, selecting low-frequency data, preprocessing the low-frequency data, and converting the selected data into a four-dimensional tensor containing total load, hour, week and month; s2, event detection is performed on the total load measurement sequence by using a time window, a four-dimensional matrix containing event amplitude and time reference is generated, events are grouped by using a heuristic grid clustering algorithm, and different clustering results represent different states of equipment in an operation process; s3, constructing a state transition matrix according to the event grouping result and the state change of each device in the operation process; and according to the energy consumption period and the state transition matrix of the equipment, reconstructing an energy consumption sequence of the equipment, completing the estimation of the energy consumption of the equipment, and calculating the use frequency of the equipment. The household data processing method has high precision and efficiency in household data processing, and can effectively separate electric energy loads of various types of electric appliances.

The invention provides a virtual power plant baseline load measurement and calculation method based on multi-dimensional factors, and the method specifically comprises the steps: screening load prediction correlation factors based on historical demand response information, and determining the correlation degree between each load prediction correlation factor and a load demand; setting a weight coefficient of each load prediction association factor based on the association degree, and constructing a prediction training data set according to the corresponding weight coefficient; an LSTM model is constructed, training is performed through the prediction training data set, model parameters are optimized through a sparrow optimization algorithm, and a baseline load measurement and calculation model is obtained; and calculating the baseline load of the virtual power plant in the target time period according to the baseline load measurement and calculation model. Baseline load prediction can be performed through the LSTM model, and parameter optimization is performed by using a sparrow optimization algorithm in the model training process so as to efficiently and accurately set LSTM network parameters, and at the same time, the measurement and calculation precision and the measurement and calculation efficiency of the baseline load are ensured.

Methods and systems for controlling the towing of a trailer by a vehicle are provided. Sensors are configured to acquire sensor data about the vehicle and the trailer. The non-transferable, computer-readable storage medium is configured to store parameters that include the dimensions of the vehicle, the trailer, or the coupling of the trailer to the vehicle via a trailer hitch. A processor is coupled to the sensors and the non-volatile, computer-readable storage medium and is configured to at least determine, using the sensor data and the parameters from the non-volatile, computer-readable storage medium, when trailer instability is likely to occur at a future time; and to execute vehicle actions according to the instructions provided by the processor when it is determined that trailer instability is likely to occur at that future time.

The invention provides a traffic load balancing method and device, electronic equipment, a storage medium and a product. The method comprises the following steps: receiving a message; the message carries a flow identifier of the AI large model training data flow to which the message belongs; if the flow identifier or the outlet port corresponding to the flow identifier is not queried in the forwarding record table, selecting a target outlet port with the maximum available bandwidth from the outlet ports meeting the transmission condition of the data flow to forward the message so as to realize the flow load balancing of the outlet ports; the aging time of the forwarding record table item is set to cover one iteration period of AI large model training. According to the method, the data flow does not need to be segmented at a time interval, a proper port can be selected to forward the data flow based on the real available bandwidth of the output port, the bandwidth and queue size of the port are not measured in real time, the accuracy of load measurement is improved, the load balancing effect is improved, network congestion caused by flow load imbalance of AI large model training is avoided, and the network performance is improved. And the resource matching efficiency of the whole service flow is improved.

The invention relates to the technical field of power system data processing, in particular to an optimal false data injection attack method and system for load-frequency control in a power system, and proposes time domain formalized modeling to find an OFDIA, minimize successful attack time, construct an OFDIA model and optimize load attack quantity; load measurement values of the whole power grid are considered in a compromise mode, the influence of power system parameters on successful attacks is analyzed, and a load frequency model of the power grid is modeled; modeling the dynamic behavior of the power system in the time domain optimization framework; and establishing a false data injection attack model, constructing an OFDIA model, and optimizing the load attack quantity. According to the method, under the condition that an attacker completely accesses the data of the power system, the damaged measurement number and the starting time are reduced, meanwhile, the attack concealment is ensured, consideration is provided for a defense mechanism of a control center, and safe operation of a power grid is ensured.

To enhance proper accuracy of load training by using proper load data in accordance with a grounding mode in walking of a subject.SOLUTION: A load measurement device comprises: a load data acquisition unit which acquires first load data of a first load sensor and second load data of a second load sensor and acquires synthetic load data of them; an analytic unit which comprises synthetic load determination means for determining whether the synthetic load data satisfies a synthetic load determination reference; and a sound output unit which generates an alarm when the synthetic load data satisfies the synthetic load determination reference. The load measurement device further comprises a load data selection unit which can select the synthetic load data, the first load data, and the second load data. The analytic unit includes individual load determination means which determines whether individual load data being the first load data or the second load data has reached an individual load determination reference. The sound output unit generates an alarm only when the individual load data selected by the load data selection unit satisfies the individual load determination reference.SELECTED DRAWING: Figure 7

A wireless scale apparatus can include a load sensor operable to be directly coupled with a portion of a load receiving element. A printed circuit board (PCB) in communication with the load sensor is operable to: measure load data from the load sensor, determine a load measurement from the load data received upon the load sensor, and transmit the load measurement.

The invention discloses a response potential model evaluation method based on construction of a load cluster, and relates to the technical field of power system management. The method comprises the steps of S1, obtaining load measurement data, S2, constructing a load decomposition model, S3, determining load curve platform power, S4, calculating demand response potential, S5, constructing user portrait feature indexes, S6, determining the demand response potential and S7, evaluating and sorting. According to the method, the response potentials of different loads can be effectively evaluated and sorted through S1-S7, and a scientific basis is provided for management, regulation and control of a power system; through the SWARA method and the CRITIC method, the subjective weight and the objective weight are obtained respectively, then the comprehensive weight is obtained, it is guaranteed that the obtained comprehensive weight is close to the subjective weight and the objective weight, the error rate of the comprehensive weight is increased, and therefore the response potential sorting and evaluation result of various loads is more accurate.

The load measuring device relates to the technical field of electric load measurement, and its structure is as follows: it is composed of a first-section gram stick, a second-section gram stick, a third-section gram stick, a meter connection line and a load measuring meter; a plug A is inserted into a socket A, and an external thread connector A is threadedly connected with an internal thread A in an internal thread connector A; a plug B is inserted into a socket B, and an external thread connector B is threadedly connected with an internal thread B in an internal thread connector B; one end of the double-head meter connection line is inserted into a socket C, and the other end is inserted into the load measuring meter. The beneficial effects of the present invention are: simple structure, quick installation, easy to carry, simple operation, safe and reliable, greatly improved work efficiency, only two people are needed to complete the work, saving manpower and material resources, ensuring personal safety, realizing ground operation of load measurement, having strong practical value, and can be promoted for use.

The invention relates to the technical field of engineering machinery, in particular to a load measuring method and system applied to a rotary platform of an excavator. The excavator revolving platform is provided with at least one target measurement area, at least one strain gauge group is arranged in the target measurement area, and the method comprises the following steps: acquiring actually measured strain data corresponding to each strain gauge group, and generating an actually measured data matrix according to the actually measured strain data corresponding to all the strain gauge groups; calculating simulation strain data corresponding to each strain gauge group according to a preset excavator model, and generating a simulation data matrix according to the simulation strain data corresponding to all the strain gauge groups; and calculating target load data of the excavator revolving platform according to the actually measured data matrix and the simulation data matrix. On the basis of the preset strain gauge group, load measurement is carried out on the external load and the inertial load of the excavator revolving platform in a mode of combining virtual simulation and actual measurement, and the position of a measurement device does not need to be iteratively adjusted for multiple times, so that the load measurement efficiency is improved.

The utility model discloses a key load testing machine, which relates to the technical field of load measurement, and comprises a base and a gantry frame arranged on the base, a Y-axis driving device is arranged in the base, the surface of the top end of the base is movably connected with a testing platform, the testing platform is in power connection with the Y-axis driving device, and the Y-axis driving device is arranged on the gantry frame. An X-axis driving device is arranged in a cross beam of the gantry rack, one side of the cross beam is movably connected with a load loading module, the load loading module is in power connection with the X-axis driving device, a Z-axis driving device is arranged in the load loading module, a test head assembly is arranged at the lower end of the load loading module, and the Z-axis driving device is in power connection with the X-axis driving device. The testing head assembly is in power connection with the Z-axis driving device; the testing machine can adapt to the testing requirements of different types of keys through the replaceable testing head and the stable connection mode, and accurate load testing is achieved.

The invention discloses a distributed cooperative measurement method and system for a load sensor array, and relates to the technical field of sensor networks and distributed measurement, and the method comprises the steps: executing the finite element simulation of a target structure, recognizing a stress key region, a boundary region and a load type, and building a structure and demand feature library; deploying a three-layer nested sensor array according to the feature library, configuring a communication protocol, and collecting data after global clock synchronization to establish a time sequence data set; and finally, outputting a load measurement result according to a cooperative authentication result through cooperative processing. The technical problems that in the prior art, a multivariable distributed measurement mechanism is lacked, intelligent sensors are insufficient in cooperation, structural load information is difficult to comprehensively and accurately obtain, and the requirements for accurate measurement and effective management and control of structural loads cannot be met are solved, and the purposes of comprehensively and accurately obtaining the structural load information and effectively managing and controlling the structural loads are achieved. And the technical effects of accurate measurement and effective management and control of the structural load are achieved.

The invention discloses a Maha-DMVAE-based power grid operation mode data iterative cleaning method and a terminal. The method comprises the following steps: collecting topological structure data and dynamic load measurement data related to a power grid operation mode; constructing a feature matrix based on a topological quantile characterization coefficient based on the topological structure data and the dynamic load measurement data; designing and training a Mahaa-DMVAE model which comprises a Mahalanobis distance measurement module by using the characteristic matrix, wherein the Mahaa-DMVAE model comprises the Mahalanobis distance measurement module; taking the adjustment of the Mahalanobis distance of the submerged space as a target, taking the feature matrix as input, and outputting a final matrix by using a Maha-DMVAE model; and based on a power flow residual value confidence dual-mode evaluation system, evaluating the effectiveness of the final matrix, if the final matrix passes the effectiveness evaluation, considering that the Maha-DMVAE model is effective, and using the Maha-DMVAE model to clean the data related to the power grid operation mode. According to the method, accurate identification and high-confidence intelligent correction of the abnormal data are realized, and the purification effect of the power grid data and the physical authenticity and availability of the final data are remarkably improved.

The present application relates to the technical field of multi-core CPU task scheduling, and discloses a multi-core CPU task scheduling optimization method based on load balancing. The method comprises continuously monitoring the output value of the load balancing indicator in the multi-core CPU task scheduler, setting the current task allocation mode as the reference task distribution when the system is balanced; collecting the real-time load measurement value of each processing core, constructing a load distribution sequence and calculating the load deviation parameter with the reference task distribution, and determining the degree of load imbalance and the skew core identifier; based on the output value of the state update indicator, generating a task reallocation instruction to adjust the task allocation direction; during task execution, real-time collection of task running data associated with a unique identifier, segmented processing according to categories, performance evaluation and storage. The method realizes accurate perception and dynamic adjustment of the load state, optimizes the task allocation logic, and improves the rationality of multi-core CPU scheduling and the running efficiency.

The application belongs to the technical field of data processing, and specifically discloses a nonlinear load measurement method, system, device and medium, wherein the method comprises the following steps: collecting physiological signal data from a multi-source sensor chain through an edge computing node, extracting key features in a time sequence by using a signal decomposition algorithm, and generating an initial load feature vector; segmenting individual motion behavior data according to the initial load feature vector, extracting motion mode features by using a sliding window technology, judging the similarity between the converted feature vector and the initial load feature vector, and determining a preliminary load match if the similarity exceeds a preset threshold; obtaining real-time environmental parameters from an external environmental data chain, and fusing the environmental parameters and the preliminary load match result by using an adaptive weight algorithm; and the application aims to solve the problems of signal noise interference, insufficient feature extraction and data fusion distortion when processing multi-source heterogeneous data in the national physical fitness monitoring and whole-population health management scenarios.

The invention relates to a microscopic and macroscopic dynamic synchronous observation method for mechanical behaviors of an ice sample. Measurement equipment adopted by the method comprises a load measurement system, a displacement measurement system and a microscopic imaging system, comprising the following steps: (1) preparing an ice sample; (2) placing a microscopic imaging system and carrying out microscopic capturing; (3) macroscopic data processing: for a Brazilian disk tensile test, recording an external load borne by the ice sample in real time through a load measurement system; a force-time change curve is generated; for a uniaxial compression test, the load measurement system and the displacement measurement system work synchronously to generate a stress-strain curve; and (4) microscomic data analysis.

The invention relates to the technical field of load measurement of engineering mechanical equipment, and discloses an excavator weighing method based on system identification, and the method comprises the steps: firstly setting working condition limitation: only a movable arm is lifted and a platform rotates, the action is stable, and the inclination of a vehicle body is less than or equal to 15 degrees; the mass and the mass center of accessories such as a hydraulic cylinder are superposed to a movable arm, a bucket rod and a bucket to obtain equivalent parameters, and a moment balance equation is established; the method comprises the following steps: collecting far-farther-middle-closer-near multi-attitude data, determining the upper and lower limits according to the physical meaning of parameters, solving by using a bounded constraint linear least square method, and substituting into a formula to calculate the mass of the material. The method is less in time consumption, and effectively improves the weighing precision and efficiency.

The present invention discloses a method and system for dynamically regulating the inter-chain interaction load in a multi-chain cross-chain scenario, which belongs to the field of cross-chain data interaction and cross-chain resource allocation of blockchains. The system of the present invention includes: a transaction request module, a load monitoring module, an execution mode selection module, and a cross-chain business execution module. The method of the present invention adopts a dynamically adjusted load measurement factor as a measurement standard, and can customize the different load types and degrees of each chain according to the load characteristics of the multi-chain system, so that the regulation method is applicable to various node types and application scenarios. The system of the present invention solves the load balancing problem of each chain in the context of cross-chain information transmission, improves the flexibility and information transmission efficiency of cross-chain and multi-chain systems, fills the gap in load allocation technology in the context of cross-chain communication, and not only has good versatility and practical value, but also has good reference significance.

The invention relates to the technical field of substation control, in particular to a dynamic load management method and system for a virtual power plant, and the method comprises the steps: collecting a to-be-managed load reactor signal; analyzing a presentation attribute of a to-be-managed load reactor signal in a time dimension, a presentation attribute of the to-be-managed load reactor signal in a wavelength dimension and a presentation attribute of the to-be-managed load reactor signal in a simulation dimension, wherein the simulation dimension is a low-dimensional feature dimension; performing index weighting operation on the presentation attribute in the time dimension, the presentation attribute in the wavelength dimension and the presentation attribute in the simulation dimension to obtain a management load value; and if the management load value meets a preset condition, determining that the to-be-managed load reactor signal is a reactor signal load, and filtering the to-be-managed load reactor signal. The transformer substation environmental load simulation analysis, determination and environmental load influence evaluation have important significance, and a load measurement result and a determination model can provide a basis for transformer substation construction and load control.

Systems and methods of performing object classification and identification at point of sale are provided. In one exemplary embodiment, a method is performed by a POS system having a load sensor and an optical sensor. The load sensor is operable to measure a load of an object while positioned on a load surface of the POS system. The optical sensor has a field of view associated with the load surface and is operable to capture an image. The method includes obtaining an image captured by the optical sensor that includes a target object and a load measurement associated with the target object performed by the load sensor while the target object is positioned on the load surface to enable object classification or identification of the target object based on object recognition of the target object from the captured image and a prediction of the target object from the load measurement.

The invention discloses a load identification method, system and device based on Radon transformation and deep learning and a storage medium, and the method comprises the steps: intercepting load measurement data, and converting the load measurement data into a load image through a Markov transfer field; de-noising processing is carried out on the load image containing noise by using wavelet transform; extracting image features of the de-noised load image by using Radon transform; dividing the image features into a training set and a test set, and performing normalization processing on the training set and the test set; and constructing a convolutional neural network, inputting the training set after normalization processing into the convolutional neural network to train the model to obtain a load identification model, testing the load identification model by using the test set after normalization processing, and performing load identification by using the tested load identification model. The method has the advantages of being easy to implement and high in recognition precision, and can be applied to the field of load regulation and recognition.

The invention relates to the technical field of dynamic load measurement, in particular to a load detection method and system for a multi-terrain damping suspension system, and the method comprises the steps: building a geometric correlation model; chassis attitude angle data and real-time suspension displacement data of the vehicle are obtained and input into the geometric correlation model, and a three-dimensional pose change vector is solved; an original strain signal is collected, dynamic signal separation is carried out in combination with the three-dimensional pose change vector, and a static load strain value is generated; performing geometric correction on the real-time suspension displacement data according to the three-dimensional pose change vector to generate a displacement characterization load value; detecting the current terrain environment type, and weighting the displacement characterization load value and the static load strain value to obtain an uncorrected real-time load value; and by taking the displacement representation load value and the static load strain value as references, learning to generate a nonlinear compensation parameter, and compensating and outputting a real-time load value in real time. According to the invention, the problem of dynamic load measurement distortion caused by multi-degree-of-freedom motion of the suspension system in a complex driving environment is effectively solved.

The application provides a flow load balancing method and device, electronic equipment, storage medium and product, comprising: receiving a message; the message carries a flow identifier of an AI large model training data flow to which the message belongs; if the flow identifier or the corresponding out port of the flow identifier is not found in a forwarding record table, the message is forwarded from a target out port with the largest available bandwidth among out ports meeting transmission conditions of the data flow, so as to realize flow load balancing of the out port; and the aging time of the forwarding record table entry is set to cover an iteration cycle of the AI large model training. The application can select a suitable port to forward the data flow based on the real available bandwidth of the out port without dividing the data flow by time intervals, instead of measuring the bandwidth and queue size of the port in real time, thereby improving the accuracy of load measurement, the load balancing effect, avoiding network congestion caused by uneven flow load of the AI large model training, and improving the efficiency of resource matching of overall business flow.

The invention provides a test apparatus, a display control method, and a computer program product. The test device includes a display control unit. The display control unit displays a load measurement value image, a load measurement chart image, and a load measurement mark image on a first area of a test monitor screen, the load measurement value image being an image indicating a measurement value of a load measured by the load measurement unit at a predetermined measurement time. The load measurement chart image is an image indicating the time series transition of the load measured by the load measurement unit during a predetermined measurement period including a predetermined measurement time point, and displays the change measurement value image, the change measurement chart image, and the change measurement mark image in a second region different from the first region. The change measurement value image is an image indicating a change measurement value measured by the change measurement unit at a predetermined measurement time point, and the change measurement graph image is an image indicating a time series transition of the change measured by the change measurement unit during a predetermined measurement period.

The invention belongs to the technical field of power data analysis, and relates to a method and system for screening steady-state operation condition periods of a thermal power generating unit. The method comprises the following steps: acquiring a load measuring point, and acquiring an analog measuring point meeting a unit load condition; selecting analog measurement points meeting set conditions from the analog measurement points, and taking the analog measurement points meeting the set conditions and the corresponding load measurement points as feature measurement points; selecting a set number of feature measurement points as a sliding window according to the time sequence, and obtaining the slope of a fitting straight line of the feature measurement points in three continuous sliding window intervals; judging the trend of the feature measurement points in each sliding window according to the slope of the fitting straight line; obtaining all upper inflection points and lower inflection points of the feature measurement points according to the trend of the feature measurement points; according to the upper inflection point and the lower inflection point, obtaining all stable time periods of the feature measurement point, obtaining an intersection of the stable time periods, and obtaining a stable working condition time period of the unit. And the stable operation time period of the unit can be accurately calculated.

The invention provides a load measurement system, a damage rate estimation system, a life prediction system, a load measurement method, a damage rate monitoring method, and a computer program product. The degree to which the load is applied to which tooth of the ring gear is measured. A load measurement system is provided with: a load detection unit that detects, in a movable part of a windmill provided with a ring gear having a plurality of teeth and a drive device, an applied load applied to the teeth of the ring gear by being applied with a driving force or an external force of the drive device via a pinion gear in a state of meshing with the pinion gear, the driving device is provided with a pinion meshed with the ring gear; and a position specifying unit that specifies, from among the plurality of teeth of the ring gear, a target tooth to which the applied load is applied.

A test apparatus includes a display controller. The display controller displays a load measurement value image indicating a measured value of a load measured by a load measurement unit at a predetermined measurement time point, a load measurement graph image showing a time-series transition of the load measured by the load measurement unit during a predetermined measurement period including the predetermined measurement time point, and a load measurement label image, in a first area of a test monitor screen. The display controller also displays a change measurement value image indicating a measured value of a change measured by a change measurement unit at the predetermined measurement time point, a change measurement graph image showing a time-series transition of the change measured by the change measurement unit during the predetermined measurement period, and a change measurement label image, in a second area different from the first area.

Provided are a service capacity load parameter reporting method and apparatus, the method comprising: a statistical capability and a reporting capability corresponding to a service capacity load parameter are issued to a network data analytics function (NWDAF); a subscription message sent by the NWDAF and used for acquiring the service capacity load parameter is received; the service capacity load parameter is determined according to the subscription message; and the service capacity load parameter is reported to the NWDAF. By means of the present invention, the problem in the related art that measuring a NF load according to a general load measurement parameter cannot accurately and real-timely reflect an NF service load change. By reporting the service capacity load parameter to an NWDAF, the NF service load change can be accurately and real-timely reflected.

The invention belongs to the technical field of data processing, and particularly discloses a non-linear load measurement method, system and device and a medium, and the method comprises the steps: collecting physiological signal data from a multi-source sensor chain through an edge calculation node, extracting key features in a time sequence through a signal decomposition algorithm, and generating an initial load feature vector; according to the initial load feature vector, carrying out segmentation processing on the individual motion behavior data, extracting motion mode features by adopting a sliding window technology, judging the similarity between the converted feature vector and the initial load feature vector, and if the similarity exceeds a preset threshold value, determining that the load is preliminarily matched; acquiring real-time environment parameters from an external environment data link, and fusing the environment parameters and a load preliminary matching result by adopting a self-adaptive weight algorithm; the invention aims to solve the problems of signal noise interference, insufficient feature extraction and data fusion distortion when multi-source heterogeneous data is processed in national physique monitoring and total population health management scenes.