736 results about "Signal wave" patented technology

An electronic device may be mounted to a main body of a removable case. The case includes a cover that rotates between open and closed positions. The device may convey wireless data and / or a control signal with the removable case over radio-frequency connectors, near-field communications (NFC) coils, connector electrodes, and / or wired data connectors. The removable case may relay the wireless data between the electronic device and a communications satellite in space. The case may include a phased antenna array in the cover. In the open position, the cover may point the phased antenna array towards the sky. The removable case may include beamforming circuitry in the cover and coupled to the phased antenna array. The control signal may control the beamforming circuitry to produce, using the phased antenna array, a signal beam oriented towards the communications satellite.

The invention relates to the technical field of fault diagnosis, in particular to an SMT production line equipment fault diagnosis method and system based on the Internet of Things, and the method comprises the following steps: obtaining multiple types of signals, aligning a time window, judging that the trend is consistent and fluctuation is synchronous to generate a sudden change event, recognizing an intersection point, extracting a key response position, and outputting an inflection point node number. And constructing a response time sequence and a propagation path, identifying abnormal nodes, and generating a fault traceability result. According to the invention, through time alignment and trend linkage identification of current, temperature and acceleration signals, fusion of trend direction judgment and fluctuation synchronization relation, a cross-equipment linkage sudden change identification mode is established, key response points are extracted through cross positioning of a jump terminal point and a vibration peak value, and a dynamic judgment mechanism of inflection point nodes is formed. In combination with a response sequential sequence and a chain path structure, local signal fluctuation analysis is converted into perception, and the judgment accuracy and traceability of abrupt change abnormity are effectively improved.

Disclosed are systems, apparatuses, processes, and computer-readable media for wireless communications. For example, an example of a process includes transmitting, to a reconfigurable intelligent surface (RIS), a plurality of reference signal beams in a plurality of directions. The process may further include receiving, from the RIS, a plurality of reflection reference signal beams in the plurality of directions based on a plurality of backtracking reflection coefficients. The process may include measuring a signal strength of each reflection reference signal beam in each direction of the plurality of directions for each backtracking reflection coefficient of the plurality of backtracking reflection coefficients. The process may further include determining, basing on measuring the signal strength, a selected beam direction from the plurality of directions and a selected backtracking reflection coefficient of the plurality of backtracking reflection coefficients.

The invention discloses a signal detrending method based on sliding window statistics and dynamic wave crest correction. The method comprises the step of realizing accurate extraction of signal trend and fluctuation characteristics through a double-window dynamic adjustment mechanism of a mean value window and a standard deviation window. A detection threshold value is dynamically adjusted by analyzing the change trend of the historical wave crest amplitude, and the real-time tracking capability of signal fluctuation is ensured; meanwhile, different parameter configurations are preset for different application scenes, the problem of missing detection or misjudgment generated when the amplitude of a fixed threshold algorithm changes suddenly is solved, and the wave crest recognition accuracy is improved. Based on a dynamic threshold algorithm, wave peak start and end points are automatically identified, a linear interpolation technology is adopted to calculate slope of each interval, fitting parameters are dynamically adjusted through residual analysis, and finally low-frequency trend terms and high-frequency characteristic components are effectively separated through difference operation of original signals and fitting signals. The problem of fitting deviation caused by non-uniform sampling can be effectively solved.

The invention discloses a distribution box operation state monitoring method and system, and relates to the field of distribution boxes, and the system comprises an acquisition module which is used for collecting current and voltage signals of each loop in a distribution box, surface temperature distribution of a box body and opening and closing state signals of a cabinet door, and converting the collected analog signals into a digital signal sequence; the extraction module is used for receiving the digital signal sequence and extracting a signal fluctuation feature, a temperature field distribution feature and a state signal change feature to generate a three-dimensional feature set; the system can obtain loop electrical parameters, box body temperature and cabinet door state in real time, accurately analyze operation characteristics to deduce state trend, quickly position defective loop components and influence range in case of abnormity, scientifically evaluate health level, timely give an early warning, synchronously disconnect power supply of associated equipment in case of severity, effectively reduce fault shutdown, and improve work efficiency. The power utilization safety and the maintenance efficiency are improved, and stable operation of the distribution box is guaranteed.

The invention discloses a power distribution network fault early warning method and system based on online monitoring, and relates to the field of fault early warning, and the method comprises the steps: continuously collecting real-time electrical signals; signal waveform prediction of the real-time electrical signal is completed according to the real-time signal prediction result, and whether an early fault signal exists in the target power distribution network is judged; if the target power distribution network has the early fault signal, obtaining power distribution network information, environment prediction data and geographic position data; constructing a topological structure of the power distribution network, and extracting early fault information of the target power distribution network; constructing an icing evolution model of the target power distribution network; completing fault risk coupling between the icing evolution model and the early fault information; and carrying out risk accumulation analysis on the topological structure of the power distribution network, and outputting fault early warning information of the target power distribution network according to a risk accumulation analysis result. According to the invention, the power distribution network fault early warning precision and efficiency can be effectively improved.

A chip-scale mode-locked laser including a cavity including a gain medium for amplifying signal electromagnetic radiation (signal) through stimulated emission, the signal comprising a signal wavelength; and a passive or active mode-locking device to enforce pulse formation in the laser. The mode-locking device includes a thin-film waveguide having a thickness on the order of the signal wavelength so as to confine and guide the signal along the thin-film waveguide, and a material comprising a second-order nonlinear susceptibility to enable active or passive mode-locking of the signal. The mode-locking device leads to generation of pulses of the signal outputted from the mode-locked laser.

The invention provides a probe pairing method for a gas ultrasonic flowmeter, which is used for testing and screening a batch of probes with the same structure and comprises the following steps of: comparing the consistency of static capacitance of the probes, primarily screening the probes, and obtaining a primarily screened probe group; comparing the consistency of the probe admittance sweep frequency curve, and determining an alternative paired probe; and comparing the consistency of output signal waveforms when the alternative pairing probes work, and judging whether the alternative pairing probes can be successfully paired or not.

The invention provides a non-contact pressure and fatigue state identification method based on double-indication joint reasoning, and relates to the field of psychological and physiological analysis, and the method comprises the steps: collecting a face visible light video and a first EDA signal; extracting an rPPG signal and a first facial behavior indication sequence; processing the signal amplitudes of the first EDA signal and the first facial behavior indication sequence to obtain a target EDA signal and a target behavior indication sequence; inputting the rPPG signal and the target behavior indication sequence into a fatigue detection model to obtain fatigue information; inputting the rPPG signal and the target EDA signal into a psychological stress detection model to obtain psychological stress information; and synchronously outputting and displaying the fatigue information and the psychological pressure information based on a preset signal waveform comparison display area. The psychological stress state and the fatigue state are analyzed at the same time, double indications are used for comprehensive consideration, cross-scene state fluctuation is identified, and the precision and efficiency of psychological stress state and fatigue state analysis can be effectively improved.

The invention provides a highway subgrade void recognition method, device and system and a storage medium, and belongs to the technical field of signal processing, and the method comprises the steps: obtaining corresponding original time domain vibration signals generated when a current vehicle passes through a plurality of grating measurement points in a grating array vibration sensing optical cable arranged below a highway surface layer; extracting dominant frequency features corresponding to each grating measuring point from the original time domain vibration signal; determining a signal fluctuation characteristic value of an area where the plurality of grating measuring points are located based on the dominant frequency characteristic corresponding to each grating measuring point; and determining a roadbed void identification result of an area where the plurality of grating measuring points are located based on the signal fluctuation characteristic values. The void identification is carried out according to the quantized data of the signal energy fluctuation between the grating measuring points, the identification mode is simple and rapid, and the fluctuation value of the dominant frequency characteristic is used as an identification index, so that the high-sensitivity discrimination of the abnormal state in the roadbed structure is realized, and the accuracy and efficiency of the void identification of the highway roadbed are improved.

The invention discloses a membrane bioreactor membrane pollution prediction method and system, and relates to the technical field of pollution detection. The method comprises the following steps: setting a frequency detection strategy, and connecting a membrane bioreactor to obtain a membrane feedback signal based on the frequency detection strategy; performing feedback signal fluctuation time sequence characteristic analysis based on the membrane feedback signal to obtain a feedback signal characteristic; the feedback signal features are combined with reactor operation parameters to be imported into a mechanism hybrid prediction model, mechanism constraint is carried out through a mechanism constraint layer according to the feedback signal features, data analysis is carried out on time series data features on the basis of the mechanism constraint through a data driving prediction layer, and a membrane state prediction result is obtained; and performing membrane pollution state analysis and progress prediction according to the membrane state prediction result, and generating a membrane pollution prediction data chain. The technical problems that in the prior art, membrane pollution prediction depends on an empirical threshold, so that recognition lags and precision is insufficient are solved, and the technical effect of improving membrane pollution prediction accuracy and real-time performance is achieved.

The invention discloses a dynamic encryption transmission method and system for sound-light alarm signals, and relates to the field of data encryption, and the method comprises the steps: obtaining a dynamic environment entropy value; generating a pseudo-random chaotic sequence; obtaining a helium-oxygen mixed gas density parameter in the dynamic environment entropy value; segmenting a preset standard alarm waveform into a plurality of signal waveforms in a time domain, and generating a distorted signal waveform according to the helium-oxygen mixed gas density parameter; performing encryption modulation on the distorted signal waveform to generate an encrypted distorted signal waveform; determining a sending sequence and a sending interval of the encrypted distortion signal waveform by combining a pseudo-random chaos sequence based on an impedance fluctuation value and background acoustic spectrum characteristics in the dynamic environment entropy; generating a dynamic modulation signal based on the transmission sequence and the transmission interval; the dynamic modulation signal is sent to a water surface console through an umbilical cable; and receiving the guide pulse, performing phase conjugation processing on the guide pulse, generating an echo verification signal, and transmitting the echo verification signal back to the water surface console.

A half-spectrum search DOA estimation method based on characteristic value gradient jump belongs to the field of array signal processing, and comprises the following steps: modeling a received signal to obtain an array output vector; calculating a received signal covariance matrix; introducing a complex conjugate covariance matrix and a scanning source to construct a new covariance matrix, and constructing a spatial spectrum function; constructing a characteristic value gradient discrimination function, and adaptively estimating a signal source number by using the characteristic value gradient discrimination function; scanning angles are traversed by using a half-spectrum search method, and a signal direction of arrival is verified and determined by combining an MVDR algorithm according to a sharp spectrum peak formed by a spatial spectrum function. According to the method, source number priori knowledge is not needed, the source number can be identified autonomously, the problem that estimation is inaccurate under complex conditions in traditional half-spectrum search is solved, and the method has good robustness under the scene of unknown source number. According to the method, the limitation that few traditional half-spectrum search angle estimation is inaccurate is overcome, and a new thought is provided for half-spectrum search DOA estimation under the condition that the number of information sources is unknown.

The present disclosure relates to an antenna layer (1) having a rear face (2) and a front face (3) and a method for producing an antenna layer (1). The antenna layer (1) comprises at least two waveguide channels (4) extending at the rear face (2), each comprising at least one waveguide hole (5) arranged at the front face (3) for transmitting and / or receiving signals. The waveguide channels (4) each comprise at least one radiation opening (6) which is arranged in the antenna layer (1) and which is interconnected to the waveguide aperture (5) by at least one radiation channel (7). A parting line (8) is arranged in the at least one radiation channel (7) between the rear face (2) and the front face (3), which parting line (8) is spaced apart from the at least one radiation opening (6) towards the at least one waveguide hole (5) by a distance (D) and preferably extends circumferentially within the at least one radiation channel (7). The present disclosure also relates to an antenna assembly (17) comprising the antenna layer (1) and an antenna arrangement (23) comprising the antenna assembly (17).

The invention discloses a data processing method based on an ultrahigh frequency original signal and a storage medium, and relates to the field of data processing, and the method comprises the steps: carrying out the adaptive gain adjustment collection of the ultrahigh frequency original signal, and enabling the signal amplitude to be stabilized in a preset effective interval through the dynamic adjustment of a gain parameter, acquiring initial acquisition data containing complete discharge characteristics; performing time-frequency domain combined noise reduction preprocessing on the initially acquired data, constructing an adaptive threshold function based on signal frequency domain distribution characteristics, and filtering background noise and non-discharge interference signal components; according to the method, the signal amplitude is dynamically stabilized through adaptive gain adjustment, it is ensured that initial collection data completely contains discharge characteristics, the problem of information loss caused by signal fluctuation is solved, the adaptive threshold is constructed based on frequency domain energy characteristics through time-frequency domain combined noise reduction, background noise and interference components are accurately filtered out, and the signal purity is improved.

The invention relates to the technical field of electrical variable measurement, in particular to a self-adaptive power quality monitoring method for a power cabinet, which comprises the following steps of: starting a low-frequency acquisition unit arranged at a monitoring node of the power cabinet, and acquiring a low-frequency coarse scanning voltage signal of the power cabinet in a current monitoring period at a preset low-frequency sampling rate; according to the method, compressed observation vectors are transmitted, sparse basis inversion calculation is executed by using an orthogonal matching pursuit algorithm, high-precision power quality time domain waveform data are reconstructed, rich high-frequency transient details are restored under the condition of low-data-volume transmission, distortion feature analysis is carried out based on reconstructed waveforms, disturbance types are identified, and a monitoring analysis report is generated and uploaded. The real-time dynamic adjustment of the sampling scale and the matrix structure along with the signal fluctuation state is realized, the optimal balance of the data compression ratio and the signal reconstruction quality is achieved, the contradiction between the storage and transmission bandwidth limitation of massive high-frequency data in a complex power grid environment is solved, and the sensitivity for transient abnormality is improved.

The invention relates to a narrow-band interference filtering method and device based on an HPLC (High Performance Liquid Chromatography) chip, and belongs to the technical field of power line carrier communication. When pulse processing is carried out on a signal, AGC / DAGC processing is paused if a narrowband interference detection starting signal is detected, a narrowband interference detection module calculates a narrowband interference frequency point by using the signal of which the AGC / DAGC processing is paused, and a filter coefficient used by a narrowband interference elimination module is determined based on the narrowband interference frequency point; and the narrowband interference elimination module carries out narrowband interference elimination processing according to the determined filter coefficient. Wherein the AGC / DAGC processed signal is paused when the signal participating in the calculation of the narrowband interference frequency point is subjected to pulse processing, so that signal fluctuation caused by AGC / DAGC processing is avoided, the calculation accuracy of the narrowband interference frequency point is improved, and the narrowband interference filtering effect is ensured.

A transmitter system comprises a mapper configured to map data bits and power information to multiple subcarriers, producing mapped information. A first-level modulator converts this mapped information into subcarrier specifications, each defined by a complex number indicating amplitude and phase. The system includes multiple data stream / power channel digital paths, each with a frequency selector that processes a portion of the subcarrier specifications. An orthogonal subcarrier generator translates these specifications from frequency to time domain, generating baseband real and imaginary signals. A second-level modulator processes these signals with intermediate-frequency sine and cosine waves to produce IF I and IF Q signals. A beamformer modifies the phase and / or amplitude of these signals across multiple antenna channels, creating directed signals. Finally, a combiner adds output signals from each data stream / power channel digital path, directing them to corresponding antenna channel modules, facilitating efficient transmission across multiple channels.

A terminal device (2) according to the present disclosure includes a control unit (203). The control unit (203) acquires, from a base station apparatus (1), information about a signal waveform for use, of a plurality of signal waveforms including a single carrier signal, the signal waveform for use being used for downlink communication with the base station apparatus (1), the information being transmitted by using a predetermined signal waveform of the plurality of signal waveforms. The control unit (203) performs the downlink communication with the base station apparatus (1) by using the signal waveform for use, on the basis of the information.

The invention relates to the technical field of fluid control, and discloses a drip-proof self-adaptive fluid dispensing control method and system. The method comprises the following steps: acquiring an image sequence, pressure data and viscosity change data when fluid is disconnected; positioning an abnormal disconnection moment, extracting a corresponding picture, and extracting a necking diameter and a necking length from the picture; calculating the real-time change rate of the necking diameter based on the necking parameters, obtaining the state identification that the fluid is about to be disconnected, and predicting the disconnection opportunity; integrating the cut-off opportunity predicted value and the viscosity data to obtain a comprehensive data set, and calibrating core parameters to generate an adaptive signal waveform; acquiring a real-time flow velocity data correction waveform, and generating an optimization control signal; and extracting a key intervention point, applying pulse intervention, calculating the colloid residual quantity, performing iterative optimization if the colloid residual quantity exceeds a preset threshold value, and performing no intervention if the colloid residual quantity does not exceed the preset threshold value, thereby finally obtaining a non-leakage control sequence. According to the method, the necking characteristic of the fluid can be accurately captured, the working condition is dynamically adapted, non-dripping dispensing is realized, and the control precision and stability are improved.

The invention relates to the technical field of textile equipment testing, in particular to a yarn textile high-speed spindle operation stability testing method and system, and the method comprises the following steps: S1, testing element layout; s2, initializing the system; s3, carrying out transient test; s4, testing a steady state; s5, interference processing: carrying out spectrum analysis on the originally acquired data, identifying interference frequency characteristics, eliminating interference by adopting a notch filtering and Kalman filtering combined method, and verifying a filtering effect; s6, parameter correlation modeling: constructing a vibration-temperature-tension-rotating speed parameter correlation model by adopting a control variable method, solving model parameters through a fitting algorithm and verifying validity; s7, quality tracing; s8, stability judgment; and S9, performing real-time monitoring and regulation. According to the method, a combined filtering scheme of notch filtering and Kalman filtering is adopted, fixed interference and random interference such as power frequency and mechanical resonance are suppressed in a targeted manner, and through comparison of locally amplified signals, the filtered signals are smooth in waveform and thorough in noise removal, and the signal-to-noise ratio and reliability of vibration detection signals are improved.

The invention discloses a high-permeability new energy power distribution network collaborative optimization method, system and device and a storage medium, and belongs to the technical field of information, and the method comprises the steps: obtaining wind power plant operation data and signal intensity, processing and fitting a signal attenuation trend, recognizing mist environment path loss, obtaining a wind power output probability distribution function, and determining an output fluctuation range. Predicting an output deviation scene, calculating a wireless signal fluctuation probability, and extracting signal fluctuation characteristics; establishing a channel fading model in combination with mist path loss, outputting wireless signal propagation delay, and determining a potential delay interval of a scheduling instruction of the energy storage system; simulating dispatch out-of-order and power regulation instruction conflicts, and generating dispatch out-of-order evaluation data; combining historical wind power output data to judge power flow fluctuation, adjust an energy storage unit response sequence, generate a power adjustment instruction sequence, calculate adjusted power flow distribution data, and generate energy storage and topology configuration optimization data, so that the operation reliability and economical efficiency of the wind power plant are remarkably improved.

The invention relates to the technical field of virtual simulation control, in particular to a Factory IO-based metal sorting control system, which comprises a virtual production line construction module, a hardware configuration module, a joint debugging module, a task execution module and a process optimization module. According to the invention, through comprehensive analysis of operation characteristics of the conveyor belt, distribution of detection stations and signal fluctuation, signal characteristics in a material coverage area can be identified in advance, associated extraction and dynamic cooperative adjustment of equipment layout and operation parameters are realized, and through interactive identification of equipment positions, adjustable areas and trigger conditions, the accuracy of the equipment layout is improved. Adjusting points influencing sorting precision are accurately positioned, task loads and priorities are intelligently matched in task execution, efficient allocation and resource optimization of scheduling areas are achieved, scheduling paths and time intervals are dynamically evaluated on the flow level, a continuous and adjustable operation sequence is formed, and sorting efficiency and overall operation performance are improved.

The embodiment of the invention discloses a commutation failure precursor detection method and system and a storage medium. The invention relates to a commutation failure precursor detection method, which comprises the following steps of: acquiring real-time electrical state data of a commutation valve from a commutation starting moment, and calculating a current change rate and instantaneous transient power according to the electrical state data; constructing an equivalent Hamiltonian operator according to the current change rate and the instantaneous transient power, solving an eigenvalue equation of the equivalent Hamiltonian operator, and obtaining an instantaneous eigenenergy spectrum; determining the occupancy probability of the current change rate and the instantaneous transient power at each energy level on the instantaneous intrinsic energy spectrum; determining a system entropy increase rate according to the occupancy probability of each energy level; according to the comparison condition of whether the system entropy increase rate is the preset threshold value or not, the existence of the commutation failure precursor is determined, so that the fault germination can be captured in advance before the electrical signal waveform is obviously distorted, the advanced detection of the commutation failure precursor is realized, and the detection sensitivity and the early warning timeliness are obviously improved.

The invention relates to the technical field of non-electrical variable control or regulation systems, and discloses an exhaust gas aftertreatment flow channel back pressure dynamic regulation method, which comprises the following steps: acquiring a supply source phase reference signal and establishing cyclic mapping; a fluid channel pressure signal pulse range change rate is extracted to determine a feed-forward factor; determining a pressure signal trough interval as an action window; determining a reference amplitude based on the feedback deviation and using a feed-forward factor for compensation to determine a target adjustment instruction; the adjusting mechanism is driven to move in the action window, so that the response peak value is locked in the trough interval, the adjusting action is locked in the low-energy phase, kinetic energy intervention of fluid pulses on the adjusting mechanism is avoided, and mechanical abrasion is reduced; pulse characteristic feed-forward compensation is utilized to enable an adjusting instruction to sense the trend of a flow field, the response speed is increased while a signal is smoothed, and pressure balance under the transient working condition is maintained.

One aspect of the data generation device of the present application is a data generation device that analogically generates data used when creating an identifier for detecting a peak observed in a signal waveform by machine learning, including: a parameter frequency information acquisition section (31, 32) that obtains frequency information of a predetermined shape parameter that characterizes the shape of a plurality of signal waveforms collected by reducing a target field for creating the machine learning of the identifier; and a simulated waveform generation section that generates a simulated signal waveform that can include overlap of a plurality of peaks and noise using the frequency information of the shape parameter, and provides the simulated signal waveform as data for training or evaluation of the machine learning. Thus, high-precision teacher data can be analogically generated.

The invention provides a multi-type demagnetization fault diagnosis method and system for a permanent magnet synchronous motor, relates to the field of motor fault diagnosis, and solves the technical problems that although the prior art does not depend on an accurate model, extracted features are often insufficient in discrimination, and fault types are difficult to accurately judge and fault magnetic poles are difficult to position. The method comprises the following steps: acquiring air gap flux density signals of the permanent magnet synchronous motor under different demagnetization faults; acquiring a flux density difference signal based on the air gap flux density signal of the demagnetization fault and the reference air gap flux density signal; dividing the flux density difference signal waveform into a plurality of waveform regions, calculating the area of the waveform region corresponding to each magnetic pole to obtain an air gap flux density waveform area difference, and calculating the fault characteristic quantity of each magnetic pole to obtain a multi-dimensional fault characteristic vector; constructing a fault classification model based on the multi-dimensional feature vectors and the corresponding fault types; and based on the air gap flux density signal and the corresponding fault degree, constructing a demagnetization degree prediction model. The method is used in a motor fault diagnosis process.

The invention relates to a coal mine underground accurate positioning card reader direction identification method, and belongs to the technical field of wireless communication and accurate positioning. In order to solve the problems of low direction identification precision and direction jump caused by dense metal supports, complex electromagnetic environment and serious multipath reflection in a coal mine in the prior art, a multi-source information fusion solution is provided. The method comprises the following steps: initiating a time of flight (TOF) ranging request through an identification card; based on the TOF distance difference interval gradient distribution weight point number, RSSI intensity difference interval differential weighting and CIR characteristic value peak-to-average ratio delay spread multipath component number, analyzing signal quality weighting, and combining historical direction information to dynamically compensate the weight point number; and finally determining the direction of the identification card by comparing the total weight points of the left and right antennas. According to the method, the direction identification accuracy in a complex mine environment is remarkably improved, the multi-path interference and signal fluctuation influence are effectively inhibited, the system anti-attenuation capability is enhanced, and the continuous stability of moving target direction tracking is guaranteed.

The invention discloses a non-invasive blood glucose calibration detection method and system based on multimode signal fusion, and relates to the technical field of blood glucose calibration of biosensors. Multimode physiological signal data are collected and filtered, original feature vectors are extracted, signal reliability is classified by adopting a random forest model, and high-quality signal subsets are screened; the method comprises the following steps of: calculating a dynamic optimization index according to real-time physiological signal fluctuation data, generating an initial weight distribution matrix, calculating a dynamic optimization index in combination with the real-time physiological signal fluctuation data, optimizing fusion parameters, and finally obtaining a comprehensive physiological feature vector through weighted summation. If the comprehensive physiological feature vector prediction deviation exceeds the limit, the signal contribution proportion is analyzed and optimized through support vector machine regression, the fusion parameters are updated according to the optimized signal contribution proportion so as to improve the calculation precision, meanwhile, the signals are classified again according to the updated fusion parameters, and a blood glucose calculation value is obtained. According to the invention, the contribution proportion of each signal is dynamically adjusted, and the stability and reliability of the blood glucose calibration process are ensured.

The invention provides a data processing method and device for an intelligent acquisition terminal, and the method comprises the steps: determining whether a current signal is in a smooth or linear change stage or a rapid change stage according to the ratio of the first-order difference to the absolute value of a preset signal change rate threshold value; according to the method, a sampling interval is dynamically adjusted according to a change condition of a signal, so that the collected data can reflect a waveform change condition of the signal, then key feature point data collected within a preset sampling duration is determined, and a data packet of a key moment where a key feature point is located is constructed; the key feature point data can reflect the amplitude and the key time domain of the signal waveform, and the characteristics of the signal waveform can be restored through the amplitude and the key time domain, so that the relatively accurate signal waveform is obtained, the distortion condition during subsequent harmonic analysis is reduced, and the accuracy of power grid state judgment is improved.