403 results about "Current sample" patented technology

The invention relates to a BUCK-BOOST converter control circuit, a control method and a safety air bag chip, the peak value of inductive current is detected through a current sampling compensation module, stable control of output voltage is achieved, the dynamic response speed is high, the loop stability is good, and meanwhile the circuit structure is simple. According to the BUCK-BOOST converter, stable switching of the working modes of the BUCK-BOOST converter is achieved through the mode control module, and it is ensured that the BUCK-BOOST converter can still work normally under the high voltage level. And the slope compensation unit is introduced into the circuit, so that subharmonic oscillation can be effectively prevented when the duty ratio of the PWM signal is greater than 50%, and the stability of the system is ensured.

The invention relates to the technical field of multi-modal sentiment analysis, in particular to a super-multi-modal sentiment analysis method and system based on bidirectional translation interaction. The method comprises the steps that historical data samples and current data samples of super-multi-mode sentiment analysis are obtained, and the historical data samples and the current data samples comprise five modes including images, audios, texts, electroencephalogram and eye movement; carrying out weighted fusion on similar samples in the historical data and the current data sample to obtain enhanced super-multi-modal features under the condition of uncertain modal deficiency; carrying out self-attention interaction on the super-multi-modal features under the condition of uncertain modal deficiency so as to improve the quality of each modal; performing splicing fusion and self-attention interaction on the four non-electroencephalogram modals to form initial fusion four modals, and translating the electroencephalogram into new fusion four modals through a multi-head attention mechanism; according to the method, the current sample and the similar sample are subjected to weighted average fusion, so that the quality of each mode is enhanced.

The invention discloses a buck-boost circuit-based mppt charging current backflow prevention control method, and relates to the technical field of switching power supplies, and the method comprises the steps: collecting a photovoltaic input voltage, a battery output voltage, and an inductive current flowing through an inductor; the current input power is calculated based on the photovoltaic input voltage and the inductive current, and the reference voltage is dynamically adjusted through an MPPT loop algorithm; pI voltage loop operation is carried out on the output voltage and the adjusted reference voltage, and expected charging current is generated; pI current loop operation is carried out on the expected charging current and the inductive current sampling value after proportionality coefficient adjustment, and a PWM duty ratio control signal is output to adjust the driving states of the four switching tubes; when the judgment circuit is in an intermittent conduction mode and meets critical conditions, a driving signal of the fourth switching tube is shielded, and only a body diode realizes a current path to prevent reverse flow of current; the battery current is effectively prevented from flowing backwards, and the system safety and the energy utilization efficiency are improved.

An intra frame prediction method and apparatus based on interpolation filtering, a video encoding method and apparatus, a video decoding method and apparatus, and a system. The intra prediction method based on interpolation filtering comprises: determining, based on a determined filtering window and a reconstructed value of a sample in a reconstruction area neighboring to a current block, a filtering coefficient used to perform interpolation filtering on the current block; and performing interpolation filtering based on a sample value of a reference sample neighboring to a current sample and the filtering coefficient, to determine a predicted value of the current sample.

The invention discloses a film capacitor enabling control method and system, a medium and a program product, and the method comprises the steps: determining current sampling data and voltage sampling data of a film capacitor in a first time period; calculating an equivalent impedance sequence within a first time length, and determining distribution characteristics of impedance components under different frequencies; dividing a plurality of frequency band intervals, and calculating an impedance change rate matrix in each frequency band interval; determining energy transmission efficiency, and determining a target frequency band interval; generating a compensation coefficient, and adjusting the amplitude and the frequency by using the compensation coefficient to obtain a target sine-wave voltage; performing energizing processing on the thin-film capacitor by adopting the target sine-wave voltage within the remaining time of the energizing duration, and calculating an instantaneous power factor in real time; and when the stability of the instantaneous power factor reaches a preset condition and the leakage current is reduced below a preset threshold value, generating an enabling completion signal. According to the invention, the adaptability between the energizing effect and the actual demand of the thin film capacitor is improved, and the energizing effect is further improved.

The invention relates to the technical field of power equipment fault diagnosis, in particular to a power transformer fault diagnosis method and system based on an improved graph convolutional network, and the method comprises the steps: obtaining a power transformer fault data set, and carrying out the preprocessing; an improved graph convolution network structure is constructed, and calculation of a graph convolution layer is improved through a self-circulation and adjacent matrix normalization method; dividing the power transformer fault data set into a training set and a test set, and performing sparse processing on an adjacent matrix; initializing the structure and parameters of the graph convolutional network; and training the graph convolutional network model by adopting a back propagation algorithm, and inputting an optimized result into a test set for verification to obtain a power transformer fault diagnosis result. According to the invention, the accuracy and efficiency of fault diagnosis of the power transformer are improved, the similarity information of the historical data and the current sample is fully utilized, and the defects that the complex nonlinear relationship is difficult to capture and the historical data is not fully utilized in the existing method are overcome.

The invention provides a method, a device and a system for online detection of arc extinguishing performance of a circuit breaker, and belongs to the field of online detection of electrical equipment of a power system. The method comprises the following steps: acquiring a circuit breaker closing current i (t); selecting a sampling point corresponding to the moment that i (t) is greater than 0.01 kA as a closing current sampling initial value for backward sampling to form a closing current sequence; performing empirical mode decomposition on each item in the sequence to obtain a closing current sequence trend item sequence, performing accumulation on each item to obtain an accumulation result k (N), and adding the accumulation result k (N) into a sequence k (n = N); when N is greater than or equal to 15, clustering the sequence k (n is equal to N) by adopting a K-means algorithm, and determining whether the number K of clustering centers is greater than 1 based on a clustering error square sum threshold condition; if not, determining that the current arc extinguishing performance of the circuit breaker is good; if the judgment result is yes, determining that the current arc extinguishing performance of the circuit breaker is abnormal; and when the arc extinguishing performance state of the circuit breaker is abnormal, generating an early warning signal for early warning prompt.

The invention relates to the technical field of power distribution network power supply, and discloses a power distribution network power supply system based on time domain control, comprising a unified time service synchronization module used for establishing a unified time service link and keeping node time synchronization; the time domain acquisition and judgment module is used for acquiring a zero-crossover timestamp and voltage and current samples and determining candidate target moments and execution modes; the instruction generation and calculation module is used for calculating a zero-crossing time difference and an instantaneous voltage difference and generating a time domain action instruction set; the starting advance locking module is used for determining and locking starting advance; the instruction rechecking judgment module is used for rechecking the effectiveness of the instruction set; the action execution checking module is used for completing loop closing or loop opening at a candidate target moment and judging a border crossing state; and the time difference updating and correcting module is used for calculating a time deviation value and updating control parameters. According to the invention, high-precision time synchronization, dynamic self-calibration and action safety coordination control of the loop closing and opening process of the power distribution network are realized.

A method and apparatus for video decoding / encoding are provided. In the provided method, a decoder obtains at least one secondary signal by applying at least one fixed filter to a primary signal. The at least one fixed filter is trained offline. The decoder obtains one or more spatially adjacent samples associated with the current sample. One or more spatially adjacent sample points are from at least one of the primary signal or the at least one secondary signal. The decoder obtains filtered sample points by applying at least one online filter to one or more spatially adjacent sample points associated with the current sample point.

The invention relates to the technical field of three-phase electric energy meters, and discloses an equivalent apparent power implementation method, device and equipment of a three-phase electric energy meter and a medium. Comprising the following steps: acquiring cyclic wave voltage sampling data and cyclic wave current sampling data of each phase of the three-phase electric energy meter in at least one cyclic wave; calculating the equivalent voltage of the three-phase electric energy meter according to the cyclic wave voltage sampling data; calculating the equivalent current of the three-phase electric energy meter according to the cyclic current sampling data; and calculating the equivalent apparent power of the three-phase electric energy meter based on the equivalent voltage and the equivalent current. According to the invention, the accuracy of apparent electric energy charging and line loss calculation can be improved.

An example method of video coding includes receiving a video bitstream comprising a plurality of frames, including a current frame comprising a current block. The method also includes determining an edge direction by performing edge detection for the current block, and determining a difference between a current sample of the current block and a neighboring sample based on the edge direction. The method further includes applying a filter to the current block based on the determined difference.

The invention provides a current sampling method, a current sampling control device and a robot. The current sampling method comprises the following steps: acquiring a first sampling value and a second sampling value which are obtained by performing current sampling on a motor by a first sampling circuit and a second sampling circuit respectively; the sampling precision of the first sampling circuit is lower than that of the second sampling circuit; and when the first sampling value is smaller than a first threshold value, performing weighted average on the first sampling value and the second sampling value by using the first weight and the second weight to obtain a current value after weighted average as a current sampling value of the motor. The current sampling precision of the motor can be improved.

The invention provides a silicon controlled rectifier dimming circuit zero crossing point detection method and system based on deep learning, and relates to the technical field of circuit zero crossing point detection. The method comprises the steps that firstly, working condition information and voltage and current signals of a circuit are obtained, time and phase information of an initial zero crossing point are recognized through a pre-trained deep learning model (a circuit zero crossing point detection model), and training data of the model comprise a large number of working conditions and voltage and current samples with labels; after the silicon controlled rectifier circuit starts to work, the system detects the stroboscopic condition, and compares the actual stroboscopic value with the standard value to obtain the deviation degree. And finally, based on the initial zero crossing point information and the stroboscopic deviation value, calculating final zero crossing point information for adjusting and optimizing the working state of the circuit. The double verification mechanism obviously improves the accuracy and reliability of zero crossing point detection, so that the conduction opportunity of the silicon controlled rectifier is more accurate, a more stable dimming effect is realized, and the influence of a stroboflash phenomenon on the illumination quality is reduced.

The invention provides a current calibration method and device, a controller and electric equipment, and the method comprises the steps: obtaining a first current during the charging and discharging of a battery, carrying out the calibration of the first current according to a fitting function, obtaining a second current, and carrying out the monitoring of the charging and discharging process of the battery according to the second current. Wherein the fitting function is determined through a current data set obtained through a data enhancement algorithm, the data enhancement algorithm comprises an SMOTE algorithm and a generative adversarial network, and used current samples are amplified when the fitting function is determined, so that the fitting function is more accurate, the current precision can be improved, the BMS current sampling accuracy is ensured, and the BMS current sampling accuracy is improved. The battery utilization rate is improved; and the safety of electric equipment is ensured.

The invention relates to a single-bus current sampling less-phase-shift phase current reconstruction method, which is based on an extended counter electromotive force (EEMF) model, utilizes coordinate transformation to design a current observer on an abc axis, and uses any phase current to estimate other two phase currents, thereby reducing wave phase shift, and reducing electromagnetic noise and power loss generated by the wave phase shift. According to the method, the calculated duty ratio is divided into five states after being centered and aligned, the phase of U, V and W corresponding to an effective current value obtained through sampling is determined according to flag bits VSector and Sshift, and if only one effective current value can be acquired, a corresponding current observer is designed, and three-phase current is reconstructed by adopting a sliding mode observer; and the reconstructed three-phase current can be distributed to U, V and W three-phase driving control circuits of the motor according to the condition of the sector, so that the effect of motor control is realized.

The present disclosure relates to a current-mode driving circuit, comprising: an output module (10) comprising a first MOS transistor (M1); a sampling module (20) comprising a second MOS tube (M2) configured to sample the current flowing through the first MOS tube (M1); the loop control module (30) comprises a third MOS transistor (M3) and a comparison module (32), and the comparison module is configured to compare the current sampled by the second MOS transistor (M2) with the reference current (Iref1) and output the compared difference value to the grid electrode of the third MOS transistor (M3), so that the first MOS transistor (M1) adjusts the output current at the output end (OUT) based on the compared difference value.

The invention discloses a residual current detection system and method based on wireless synchronization and software confluence, and relates to the technical field of residual current detection. A host central processing device receives current sampling data with timestamps from a slave central processing device through a signal receiver to complete centralized receiving of multiple paths of current signals; after the host central processing device receives synchronous current sampling data with timestamps transmitted by the slave central processing device, aligning and synthesizing multiple paths of time-synchronized current signals through a software confluence algorithm, carrying out vector summation on the multiple paths of current signals based on a vector operation principle, and calculating the vector sum of residual current; and judging whether a grounding fault or an insulation defect exists according to whether the vector sum is zero, if the vector sum deviates from the zero value, judging that residual current abnormity exists, and giving an alarm or recording fault information. The detection system effectively improves the accuracy, reliability and applicability of residual current detection.

The invention provides a strip steel hot continuous rolling industrial process monitoring method and device, and relates to the technical field of ferrous metallurgy industrial process monitoring. The method comprises the following steps: an off-line modeling stage: collecting multi-dimensional sensor data in the strip steel hot continuous rolling industrial process for standardized cleaning; carrying out data enhancement on the cleaned data by adopting DDIM; random shielding is carried out by using a feature focusing cooperation mechanism based on random shielding; constructing an unsupervised process monitoring model, and training the constructed unsupervised process monitoring model by using the data after the shielding operation; processing data reconstructed by the trained unsupervised process monitoring model by adopting a kernel density estimation method, and determining a control limit; and an on-line monitoring stage: judging whether the current sample is normal or not by using the control limit to realize abnormal working condition detection. By adopting the method, the monitoring sensitivity of the strip steel hot continuous rolling industrial process can be improved.

The invention discloses a class increment target detection method combining sample playback and an attention mechanism, and belongs to the field of target detection, and the method comprises the steps of dynamic sample selection playback, DETR model construction based on attention enhancement, and hybrid playback training. At the end of each incremental learning stage, dynamically replaying the samples, screening representative samples from the current task through a K-Center-Greedy algorithm, and storing the representative samples into a memory bank with fixed capacity; according to the DETR model based on attention enhancement, a channel attention module (SE module) is embedded in a target detection network DETR, and key feature expression is enhanced through feature channel re-calibration; the hybrid replay training is mainly characterized in that during new task training, a historical sample is extracted from a memory bank and mixed with a current sample to serve as a training set to be input, and cross-task knowledge fusion is achieved by jointly optimizing a detection loss function and an attention weight.

The invention relates to an active power factor correction device, in the active power factor correction device, an average current controller and a feed-forward compensation controller are respectively used for obtaining a first duty ratio and a second duty ratio, a duty ratio processor is used for superposing the first duty ratio and the second duty ratio to obtain a total duty ratio, the pulse width modulation controller is used for generating a pulse width modulation signal for controlling the switching device according to the total duty ratio, the second duty ratio is related to the sum of inductive currents sampled for multiple times in a power frequency period, and the sum of the inductive currents changes along with the load power of the main circuit. Therefore, the second duty ratio can reflect the dynamic change of the load power, the total duty ratio is obtained by superposing the first duty ratio and the second duty ratio, the feedback can be enhanced when the load power changes, and compared with the control by only using the average current method, the control capability on the output voltage and the input current is improved, and the control efficiency is improved. And a better power correction effect can be realized.

The invention discloses a manganin current sampling on-line self-correction method and system of an intelligent fusion terminal. The method and system are applied to the intelligent fusion terminal comprising a manganin diverter assembly. The assembly comprises a working resistor connected in series in a main current loop and a reference resistor for monitoring, the working resistor and the reference resistor are thermally coupled, and the reference resistor does not bear working current during normal sampling. The method comprises the following steps: respectively measuring real-time resistance values of the two resistors in a silent working window period; calculating a current actually measured resistance value ratio; obtaining an ideal resistance value ratio of the two in a stress relaxation-free ideal state; obtaining a correction resistance value ratio variable quantity according to a difference value between an actual measurement ratio and an ideal ratio; and finally, calculating a correction coefficient and updating a sampling channel parameter so as to compensate resistance drift caused by long-term electric thermal stress and realize automatic correction of subsequent current sampling. According to the method, on-line and high-precision self-correction independent of an external reference is realized, and the problem of long-term stress relaxation of a manganese-copper material is effectively solved.

The invention relates to the technical field of signal processing, and particularly provides a full-quantization spectrum characteristic statistical method, system and device and a storage medium, and the method comprises the steps: discretizing a current sampling signal frequency band into a continuous frequency point unit sequence according to a preset rule, and mapping a signal intensity value into an intensity level according to the preset rule; if the signal intensity exceeds the current noise base value, determining the frequency point range of the current sampling signal by extracting the center frequency point and the effective bandwidth of the current sampling signal, and recording the intensity level mapped for all frequency point units in the range once; if the signal intensity does not exceed the current noise base value, recording the intensity grade of mapping for one time for a frequency point unit in the frequency point unit sequence of the current sampling signal; and counting all involved frequency point units in the frequency spectrum recording process and the occurrence frequency of each intensity level recorded on each frequency point unit. According to the invention, the problem of virtual high background noise caused by a traditional peak value holding mode is solved.

A method comprising emulating (401) an implementation of a post-processing process of an SL-HDRx system before applying a pre-processing process of the SL-HDRx system using input color components of a current sample of a current picture up to a computation of at least one intermediate chroma component; determining (402, 404) that a value of the at least one intermediate chroma component is higher than a maximum chroma component value depending on a calculation precision set in the implementation of the post-processing process; applying (403, 405) a correction process on the input color components to obtain corrected color components for the current sample respecting at least a clipping prevention condition responsive to the value of the at least one intermediate chroma component is higher than the maximum chroma component value.

Embodiments of the disclosure provide a system and method of operating a power tool. The method includes measuring a battery current draw, sampling the battery current draw to generate a plurality of battery current samples, calculating an averaged current value by averaging the plurality of battery current samples, and comparing the averaged current value with a predetermined current value. The method also includes determining a number of motor revolutions, comparing the number of motor revolutions to a startup threshold, and determining a cycle is complete and stopping the motor when the number of motor revolutions exceeds the startup threshold and the averaged current value is greater than the predetermined current value.

The invention discloses an asynchronous motor rotor broken bar fault detection method and system based on a second derivative, and the method comprises the following steps: S1, obtaining a stator current sampling data sequence # imgabs0 # of any phase of an asynchronous motor, the # imgabs1 # being an nth current signal; s2, carrying out fundamental frequency suppression on the stator current sampling data sequence # imgabs2 by using a second derivative, and constructing an edge frequency function sequence # imgabs3 #, wherein # imgabs4 # is the nth edge frequency function; s3, carrying out fast Fourier transform on the side frequency function sequence # imgabs5 # to extract a side frequency characteristic frequency spectrum; and S4, judging whether the asynchronous motor has a rotor broken bar fault or not according to the side frequency characteristic spectrum. The invention aims to simplify signal acquisition required by fault detection and accurately extract the side frequency characteristic frequency spectrum reflecting the rotor broken bar fault so as to accurately diagnose the rotor broken bar fault of the asynchronous motor.

The invention discloses a switching power supply and an average current sampling circuit thereof, and the circuit comprises a real-time current sampling circuit (1) which samples the real-time current flowing through an upper switch (NM1) / lower switch (NM2); a holding signal generation circuit (3) for generating the holding signal at more than half of the time of each conduction period of a first control signal / a second control signal on the basis of the first control signal of the upper switch (NM1) / the second control signal of the lower switch (NM2), the conduction period being a time period in which the control signal controls the corresponding switch to be conducted; the sampling and holding circuit (2) is used for receiving the holding signal and holding and outputting the current sampled by the real-time current sampling circuit (1) at the half conduction period moment; according to the invention, the sampling current is enough for the establishment of the sampling circuit from the inductive current at the beginning of the sampling conduction period to the more than half time of the conduction period, so that the error caused by the establishment time is avoided, and more accurate inductive average current sampling is realized.

The invention provides a charging pile verification method based on wireless communication, and the method comprises the steps: carrying out the data preprocessing of obtained multi-source operation data of a target charging pile, obtaining synchronous data with a timestamp, and enabling the synchronous data to comprise a voltage sampling data set, a current sampling data set, and an electric energy pulse data set; performing data encapsulation based on the synchronous data to obtain a transmission data packet, and sending the transmission data packet to a verification terminal through a wireless network; in response to the transmission data packet received by the verification terminal, carrying out data buffering and reordering on the transmission data packet based on the timestamp, and generating ordered time sequence data; based on the ordered time sequence data, time axis reconstruction and interpolation alignment processing are carried out, and an alignment data matrix is generated; and performing electric energy metering error analysis based on the alignment data matrix to obtain a charging pile verification result. By adopting the method, the accuracy and reliability of remote verification of the charging pile can be improved.

The embodiment of the invention relates to the technical field of wireless power supply, in particular to a voltage compensation method. The method comprises the steps of obtaining a target line resistance value and a target temperature coefficient, determining a calibration current which is obtained by calibrating an output current sampled by the wireless power supply system, determining a loss compensation value based on the target line resistance value and the calibration current, compensating the loss compensation value based on the target temperature coefficient, and outputting the compensated loss compensation value. Obtaining a voltage compensation value, determining a target voltage based on the voltage compensation value and a preset voltage value, and controlling the wireless power supply system based on the target voltage. According to the embodiment of the invention, the loss compensation value can be obtained according to the calibration current and the line resistance value to compensate the output voltage of the wireless power supply system, and the loss compensation value is corrected through the temperature coefficient to obtain a more accurate voltage compensation value, so that the output voltage of the system is more accurate, and the operation reliability and safety of equipment are improved.

The invention discloses a control method and device of a power supply system and the power supply system, and belongs to the technical field of power supply. The power supply system comprises power supply equipment and power metering equipment, the power supply equipment is connected with a grid-connected point, the power metering equipment is arranged at the grid-connected point, and the method comprises the following steps: controlling each phase of the power supply equipment to output power under the condition that the grid-connected point is matched with the phase of each phase voltage sampling line wiring of the power metering equipment; acquiring a current sampling power value of the power metering equipment; based on the current sampling power value and the power value of the power output of each phase of the power supply equipment, determining the phase matching condition of the grid-connected point and each phase of current sampling line wiring of the power metering equipment; and under the condition of phase sequence misconnection between the grid-connected point and the current sampling line, based on the phase matching condition of the grid-connected point and the wiring of each phase of current sampling line, adjusting the sampling output information of the power metering equipment. When the phase sequence between the grid-connected point and the current sampling line is misconnected, correct power data can be obtained without manually changing the wire harness.

The invention discloses a method for evaluating the residual service life of a bearing, and particularly relates to the technical field of bearings, which comprises the following steps of: applying a common-mode voltage of a simulation inverter driving motor to an intact bearing until the bearing is invalid so as to observe a key event of severely damaging the bearing; acquiring data of vibration, current and temperature in the process from operation to failure of the bearing to obtain original vibration, current and temperature samples; determining a discharge event in the original current sample based on a wavelet decomposition method; key vibration characteristics in the original vibration sample are extracted based on a time domain statistical moment method; based on the temperature data, the key vibration characteristics and the discharge event, a prediction result of the residual life of the bearing is obtained by using an extended Kalman filtering method; using the surge of the bearing discharge event as a cue to start estimating the bearing RUL, this new RUL estimation algorithm provides a more accurate result than the RUL estimation starting from the bearing life, and requires less computational time.