140 results about "Fourier analysis" patented technology

Electroporation-based therapies (EBTs) employ high voltage pulsed electric fields (PEFs) to permeabilize tumor tissue, resulting in changes in passive electrical properties detectable using electrical impedance spectroscopy (EIS). Currently, commercial potentiostats for EIS are limited by impedance spectrum acquisition time (˜10 s); this timeframe is much larger than pulse periods used with EBTs (˜1 s). Fourier Analysis SpecTroscopy (FAST) is introduced as a methodology for monitoring tissue inter-burst impedance (diagnostic FAST) and intra-burst impedance (therapeutic FAST) during EBTs. FAST is a rapid-capture (<<1 s) technique which enables monitoring of inter-burst and intra-burst impedance during EBTs in real-time. FAST identified a frequency which delineates thermal effects from electroporation effects in measured impedance. Significance: FAST demonstrates the potential to perform EIS, in addition to intra-burst impedance spectroscopy, using existing pulse generator topologies.

The invention discloses a new energy station harmonic emission level evaluation method and system based on recording data, and the method comprises the steps: carrying out the wavelet threshold de-noising processing of the recording data of line current and bus voltage in a power grid, and then carrying out the Fourier analysis, and obtaining the amplitude and phase angle of each harmonic current and voltage; on the basis of the amplitude and phase angle of each harmonic current and voltage, the harmonic order to be analyzed is determined through the harmonic voltage content rate and the harmonic distortion rate, an abnormal bus is screened as a concerned bus, and suspicious harmonic source users in the power grid are identified; establishing an equivalent model of the power grid, and solving harmonic transfer impedance between each suspicious harmonic source user and the concerned bus in the equivalent model by using a blind source separation algorithm; and quantifying the harmonic responsibility of each suspicious harmonic source user to the concerned bus. According to the invention, the accuracy of harmonic evaluation and the accuracy of tracing are improved, and the improvement of the electric energy quality of a new energy station and the stable operation of a power grid are facilitated.

Electroporation-based therapies (EBTs) employ high voltage pulsed electric fields (PEFs) to permeabilize tumor tissue, resulting in changes in passive electrical properties detectable using electrical impedance spectroscopy (EIS). Currently, commercial potentiostats for EIS are limited by impedance spectrum acquisition time (˜10 s); this timeframe is much larger than pulse periods used with EBTs (˜1 s). Fourier Analysis SpecTroscopy (FAST) is introduced as a methodology for monitoring tissue inter-burst impedance (diagnostic FAST) and intra-burst impedance (therapeutic FAST) during EBTs. FAST is a rapid-capture (<<1 s) technique which enables monitoring of inter-burst and intra-burst impedance during EBTs in real-time. FAST identified a frequency which delineates thermal effects from electroporation effects in measured impedance. Significance: FAST demonstrates the potential to perform EIS, in addition to intra-burst impedance spectroscopy, using existing pulse generator topologies.

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The invention discloses a six-winding high-voltage variable-frequency speed regulation control method and system, and belongs to the technical field of high-voltage variable-frequency speed regulation, and the method comprises the steps: building an electric-thermal-magnetic coupled six-dimensional nonlinear system model through collecting the structural parameters, thermosensitive data and an initial state of a motor; establishing a frequency domain regulation and control matrix among the six windings in combination with the operation condition and the load type; predicting a future disturbance power trend by using a weighted short-time Fourier analysis method, dynamically correcting the reference current of each winding, and generating six groups of PWM control signals; when the performance of the winding is degraded, fault-tolerant topology reconstruction and driving task redistribution are executed; periodically reconstructing a control matrix through a thermoelectric feedback mechanism, and executing parameter adaptive optimization according to a current balance coefficient and hot redundancy distribution; according to the method, high-precision current coordination control, frequency domain energy decoupling and winding thermal load balancing can be realized, and the speed regulation response speed, the stability and the fault-tolerant capability of the system are remarkably improved.

The invention discloses a gear meshing noise evaluation method based on a gear transmission error curve. The gear meshing noise evaluation method specifically comprises the following steps of 1, obtaining tooth surface waviness based on a gear measurement center; step 2, synthesizing a whole tooth surface waviness curve of the gear; 3, gear transmission error calculation based on an envelope line; 4, carrying out Fourier analysis on the gear transmission error curve based on sine fitting; step 5, calculating an order spectrum; step 6, abnormal order analysis; a gear transmission error curve can be decomposed into harmonic components with different frequencies through sine fitting Fourier analysis, and each harmonic corresponds to a specific order in a gear error. The abnormal order can excite vibration of a specific frequency, and when the gear noise problem is analyzed, the step of recognizing and eliminating the abnormal order is a key step.

The invention provides a new energy field grid-connected system broadband oscillation wide-area propagation path tracking method and device, and the method comprises the steps: firstly obtaining an electrical main wiring diagram of a transformer substation, numbering incoming and outgoing lines, and recording the rated voltage and capacity of the incoming and outgoing lines; and monitoring harmonic voltage and current of the high-voltage bus and the low-voltage bus of the transformer substation, carrying out fast Fourier analysis, and judging whether oscillation occurs or not. If oscillation occurs, the concerned oscillation spectrum range and harmonic wave type are determined, and the sampling frequency is determined. Then, a sampling instruction is issued, voltage and current data of all lines are collected, and per-unit processing is carried out; and performing Fourier series analysis on the data to obtain a harmonic spectrogram. And finally, determining an oscillation propagation path in combination with the main wiring diagram, the operation mode and the spectrogram so as to quickly position disturbance sources, quantify responsibilities of multiple disturbance sources and improve system stability.

This application relates to the field of electrical technologies, and provides a full even harmonic digital demodulation method based on full-phase analysis for a magnetic modulator. According to the full even harmonic digital demodulation method based on full-phase analysis for a magnetic modulator, standard voltage timing data output by the magnetic modulator is obtained when a DC calibration current with a set amplitude is fed into the magnetic modulator during calibration of the magnetic modulator; an output voltage sequence from full-phase Fourier analysis is established based on the standard voltage sequence data, and the output voltage sequence is preprocessed; comprehensive analysis is performed on the preprocessed output voltage sequence from full-phase Fourier analysis to obtain all standard even harmonic signals and current conversion coefficients.

The present invention discloses a gear meshing noise evaluation method based on a gear transmission error curve, specifically comprising the following steps: Step 1: Acquisition of tooth surface waviness based on the gear measurement center; Step 2: Synthesis of the gear full tooth surface waviness curve; Step 3: Calculation of gear transmission error based on the envelope; Step 4: Fourier analysis of the gear transmission error curve based on sine fitting; Step 5: Calculation of the order spectrum; Step 6: Analysis of abnormal orders. The gear transmission error curve can be decomposed into harmonic components of different frequencies through sine fitting Fourier analysis, with each harmonic corresponding to a specific order in the gear error. Abnormal orders can excite vibrations of specific frequencies. Identifying and eliminating abnormal orders is a key step in analyzing gear noise problems.

The invention relates to the technical field of power grid safety evaluation, in particular to a power system short-circuit parameter prediction method, system and device based on time-space relevance and a storage medium. A multi-dimensional state vector including a node voltage vector, a branch current vector, a short-circuit impedance matrix, spatial position information and a time feature vector is constructed, and a space-time correlation feature vector including a time-dimensional feature, a spatial-dimensional feature, a space-time coupling feature and a state feature is extracted. Wavelet transform, Fourier analysis and graph theory analysis are adopted to identify a parameter change rule and a propagation effect. A multi-level prediction model of a statistical prediction layer, a deep learning layer and a fusion layer is constructed, and comprehensive description of dynamic characteristics of short-circuit parameters is realized through spatio-temporal feature fusion. A staged training strategy is adopted, and comprises the steps of establishing a basic model through offline training, updating parameters in real time through online learning, and quantifying uncertainty through a probability prediction framework. And a prediction correction mechanism and a reliability evaluation system are established, and a complete prediction-evaluation-correction closed loop is formed.

The invention relates to the technical field of ship navigation behavior prediction, and discloses a ship navigation behavior prediction method and system based on interpretable artificial intelligence. Comprising the following steps: acquiring ship AIS historical data and historical marine environment data in a target sea area; based on a time scale and a space scale, fusing the ship AIS historical data and the historical marine environment data, and constructing a spatio-temporal data set; performing feature decoupling on a static variable and a time-varying variable of the spatio-temporal data set, and determining historical input data, known future input data and static input data; an interpretable space-time fusion neural network model is constructed based on a dynamic gating residual neural network, a space-time characteristic variable selection network, a Fourier analysis gating neural unit and an interpretable multi-head attention mechanism so as to accurately predict ship navigation behaviors such as a ship trajectory, an over-the-ground navigational speed and an over-the-ground course. And a navigation behavior influence factor weight visualization result is output, and the method has interpretability.

To provide a photoelectric conversion element improved in durability.SOLUTION: A photoelectric conversion element has a first electrode, a second electrode, and a photoelectric conversion layer arranged between the first electrode and the second electrode and including a crystal of a perovskite structure. The photoelectric conversion element has, between the photoelectric conversion layer and the first electrode, a charge transport layer. The charge transport layer contains a charge transport substance and insulating resin that are phase separated. The ratio of the volume of an area of the charge transport substance to the volume of an area of the insulating resin is 5 or more and 30 or less. In a binarized image of the two-dimensional space distribution of an area A and an area B obtained by measuring the charge transport layer with an optical microscope, when a value that is obtained through Fourier analysis on the binarized image and that is determined by the following calculation method for D is defined as D μm, D μm satisfies 4≤D≤12.SELECTED DRAWING: Figure 1

The invention discloses a stacked steel plate counting method and system based on machine vision. The stacked steel plates can be accurately counted. The counting method comprises the following steps: firstly, scanning the side surfaces of stacked steel plates by using a linear array camera to obtain a steel plate end surface complete image, and intercepting a steel plate area according to gray and texture differences between the steel plates and a background image; denoising and enhancing the steel plate end face image, and detecting upper and lower edge lines of the steel plate to obtain a steel plate edge graph; and finally, projecting the edge image along the edge direction, obtaining the thickness of the steel plate by using Fourier analysis, fusing thickness information into a peak detection algorithm, eliminating missing detection or excessive detection caused by imaging interference, and realizing accurate counting of the steel plate. The movable steel plate counting system is composed of the high-resolution camera, the light source, the polaroid, the industrial personal computer, the displayer, the power source and the motor lead screw transmission mechanism and has the advantages of being convenient to operate and efficient in counting, and the accuracy and reliability of the steel plate counting system are improved.

The invention provides a data prediction method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining to-be-predicted data, and determining a first projection result based on the to-be-predicted data; performing Fourier feature extraction on the first projection result to obtain a first Fourier feature, and performing nonlinear activation feature calculation on the first projection result to obtain a first nonlinear activation feature; based on the first Fourier feature and the first nonlinear activation feature, determining a first Fourier analysis network output feature; and based on the first Fourier analysis network output feature, determining a target Fourier analysis network output feature of the to-be-predicted data, and calculating a target predicted value of the to-be-predicted data by using the target Fourier analysis network output feature. According to the embodiment of the invention, the accuracy of data prediction can be effectively improved.

The invention provides a control method and device for improving the sub-super-synchronous stability of a following grid energy storage converter, belongs to the field of power grid equipment control, and aims at solving the problem that an existing control mode is insufficient in the aspect of improving the sub-super-synchronous oscillation suppression capability, and the invention provides the control method and device for improving the sub-super-synchronous stability of the following grid energy storage converter. Comprising the following steps: carrying out Fourier analysis on an obtained alternating current port voltage instantaneous value to obtain a voltage component amplitude of each frequency, carrying out per-unit processing, and judging whether the frequency is an oscillation frequency or not; the suppression voltage is generated by adopting double proportional-integral control, and the generated suppression voltage is superposed with the conventional generation voltage of the grid-following energy storage converter to generate a reference value of the modulation system; and generating trigger pulses of each IGBT in the grid-following energy storage converter by adopting PWM (Pulse-Width Modulation). According to the invention, each oscillation harmonic can be flexibly suppressed only by using the oscillation harmonic voltage, and the sub-super synchronous stability performance of the grid-following energy storage converter is remarkably improved.

The invention discloses a colon adenoma identification method and device based on Mueller matrix polarization measurement and regularization, a storage medium and electronic equipment. The method comprises the following steps: acquiring a polarization image corresponding to a fresh medical sample containing colon adenoma and normal tissue through a light polarization system, and preprocessing the polarization image; fourier analysis is carried out on a detection signal in the light polarization system to obtain a Mueller matrix, and a Lu-Chipman polarization decomposition algorithm is used for carrying out polarization decomposition on the Mueller matrix to obtain three polarization decomposition parameters; obtaining polarization data of a plurality of channels based on the Mueller matrix, and constructing a sample set based on the polarization data; constructing a target function based on the projection function and the sample set, solving the target function to obtain an analytic solution of the optimal projection direction, and calculating a characteristic value based on the analytic solution of the optimal projection direction; and classifying the polarization images corresponding to the fresh medical samples of the colon adenoma and the normal tissue based on the feature values to obtain a classification result. The lesion recognition rate can be improved.

The invention relates to the technical field of geological disaster assessment, in particular to a seafloor landslide mass stability assessment method based on multi-source geophysical data, which comprises the following steps: S1, acquiring multi-beam sounding, side-scan sonar, seafloor seismograph and sediment columnar sample data, completing space-time registration, and performing equivalent density conversion on acoustic wave impedance and shear wave velocity to obtain an acoustic wave impedance and shear wave velocity; constructing a three-dimensional grid model; s2, based on the three-dimensional grid model, calculating a curvature mutation index by adopting sliding window Fourier analysis, calculating a pressure gradient in combination with pore water pressure data, and generating a characteristic parameter matrix composed of density, curvature and pressure gradient; and S3, based on the characteristic parameter matrix, calculating shear strain energy and gravitational potential energy superposition field intensity, and generating a landslide mass stability map taking the instability probability as an index. According to the invention, a visual three-dimensional landslide mass stability map is constructed, and high-precision identification and three-dimensional early warning of submarine landslide risks are realized.

The application provides a method and device for graph data processing, and relates to the technical field of artificial intelligence, and the method comprises: a method for graph data processing, which comprises the following steps: acquiring graph data, extracting the basic structure features of the graph data through a static topology path, adaptively screening the key neighbor features in the graph data based on an attention mechanism and in combination with the basic structure features through a dynamic path, establishing long-distance semantic association between nodes through topology-aware coding based on the basic structure features and the key neighbor features through a linear graph transformer with O ( n ) of linear complexity, and establishing long-distance semantic association between nodes through topology-aware coding; performing frequency domain projection on the node features to generate frequency domain features, explicitly extracting and enhancing the periodic discriminant components in the frequency domain features through a Fourier analysis network to generate graph neural network data. Thus, the graph representation learning capability of the graph neural network is effectively improved.

The invention discloses a method for carrying out full-superconducting cyclotron magnetic field shimming based on target first harmonics. Comprising the following steps: determining distribution requirements of target first harmonics; determining a superconducting coil group for generating a target first harmonic; forming the superconducting coil group by a group of coils; the positions and the number of radial measuring points and the total harmonic component number n are determined, and based on Fourier analysis, a first harmonic shimming matrix A based on the unit current adjusting quantity, the total harmonic component n and the total adjusting scheme number m is established; based on Fourier analysis, establishing a target first harmonic amplitude matrix B based on the total harmonic component n; a shimming equation B = AX is listed, X is solved, and X is a matrix of superposition coefficients of the adjustment scheme; according to the invention, magnetic field shimming is carried out by taking one coil group as a unit, and primary harmonics formed by one coil group can better express the distribution shape of the magnetic field, so that a conventional panel shimming method can be better replaced.

The invention discloses an LC resonant converter control method, which relates to the technical field of LC resonant converters, and comprises the following steps: obtaining basic parameters of each part of the LC resonant converter, obtaining a state equation of each part according to the obtained basic parameters, and when the LC resonant converter is disturbed, determining the state equation of each part according to a disturbance signal received by the LC resonant converter. Obtaining each state variable in the resonant network module; all the state variables are substituted into the state equations, and steady-state solutions corresponding to all the state equations of the LC resonant converter in the steady-state state are obtained; according to the method, time domain signals are analyzed by means of a Fourier analysis method, approximate processing is carried out on harmonic waves of all orders, the method has high accuracy, an equivalent circuit model of the converter in a steady state can be established, in addition, simulation analysis does not need to be carried out on a circuit, and only steady-state signals under the action of non-modulation signals need to be known.

The present application relates to the technical field of image processing, and more particularly to a self-adaptive periodic background elimination method based on Fourier analysis, comprising the following steps: step one, image input; step two, horizontal and vertical frequency division; step three, respectively performing inverse color, enhancement and normalization preprocessing operations on the horizontal frequency graph and the vertical frequency graph; step four, performing Fourier transform on the image of step three, and performing Fourier transform on the horizontal frequency preprocessed graph and the vertical frequency preprocessed graph; step five, obtaining high-amplitude phase difference of the image of step four; step six, obtaining horizontal and vertical phases; step seven, high-response point elimination; step eight, inverse Fourier transform, performing inverse Fourier transform on the separated frequency response graph and phase response graph in step seven; and step nine, feature recognition; the algorithm of the present application can automatically identify the periodic grid background on the liquid crystal panel, automatically eliminate a number of frequency parts with the highest response in the horizontal and vertical directions, and the remaining non-periodic features after elimination are defects.

The present invention discloses a method and system for measuring railway mileage based on Fourier analysis; the present invention relates to the field of railway signal technology; S100, Fourier transform: for discrete time domain signal x[n], discrete Fourier transform (DFT) is performed to obtain spectrum data X[k]:; wherein, N is the number of time domain signal samples; k is the index of the frequency domain; i is the imaginary unit; e is the base of the natural logarithm; S101, time-frequency analysis: short-time Fourier transform (STFT) operation is performed to provide information of the signal in the time domain and frequency domain, and the spectrum data X[k] is corrected to be new spectrum data X[k,t]; the present invention calculates the power spectrum density of the signal in real time, and dynamically adjusts the preset threshold value T according to its statistical characteristics, and the present invention can adaptively process various signal conditions. Avoid causing the system to erroneously judge the insulation node that the train is currently passing through, thereby affecting the subsequent positioning, mileage correction and error accumulation.

The present disclosure provides a method for locating and detecting a high-resistance grounding fault of a grid-connected photovoltaic transformer winding, comprising: measuring the voltage to ground of the starting end and the neutral point of the three-phase winding; calculating the voltage phasor corresponding to the voltage to ground at the inverter switching frequency based on a fast Fourier analysis algorithm; calculating the negative-sequence component and the zero-sequence component of the voltage at the starting end of the three-phase winding at the inverter switching frequency according to the voltage phasor; obtaining the negative-sequence voltage ratio and the zero-sequence voltage ratio at the inverter switching frequency according to the voltage phasor corresponding to the negative-sequence component, the zero-sequence component and the voltage phasor corresponding to the neutral point voltage to ground; judging the phase difference, the distribution position along the winding and the degree of fault development of the transformer winding high-resistance grounding fault according to the negative-sequence voltage ratio and the zero-sequence voltage ratio. The present disclosure also provides a device for locating and detecting a high-resistance grounding fault of a grid-connected photovoltaic transformer winding.

The present invention discloses a method and system for identifying a secondary silicon steel sheet dry-type transformer. The method comprises the following steps: performing no-load tests on a dry-type transformer to be identified and a brand-new dry-type transformer of the same model, and collecting two noise audio segments emitted by the two dry-type transformers at this time; performing short-time Fourier analysis on the noise audio to obtain the sound wave amplitude corresponding to each frequency, taking the 50 Hz frequency-multiplied sound wave amplitude therein to calculate the fundamental frequency energy proportion, spectrum complexity, and high-to-low frequency energy ratio of the dry-type transformer; calculating the deviation rate of the fundamental frequency energy proportion, spectrum complexity, and high-to-low frequency energy ratio between the brand-new dry-type transformer and the transformer to be identified, and judging whether the transformer to be identified is a secondary sheet transformer by comparing the deviation rate with a set threshold. The system and the method are based on the same concept. The present invention efficiently and accurately judges whether a transformer is a secondary silicon steel sheet transformer without disassembling the transformer, thereby improving the inspection efficiency of the transformer and reducing the labor and material costs required for random inspections.

The present invention relates to a method and system for extracting radar target motion characteristics. The method includes preprocessing radar one-dimensional range profile data to obtain the phase signal of the target; using empirical mode decomposition to separate the signal of the phase signal to obtain a plurality of intrinsic mode functions; and performing motion parameter estimation on the intrinsic mode functions respectively based on the spectrum analysis method of Fourier analysis to obtain the radar target motion characteristics. The present invention can adapt to the actual situations of more diverse, high-speed motion, and motion coupling of radar targets, and the extracted target motion characteristics have higher accuracy.

This invention discloses a specific harmonic cancellation pulse width modulation method suitable for digital power amplifiers. It involves fitting a periodic signal f(t) to obtain an approximate function g(t) and performing Fourier analysis to derive the Fourier coefficients b of the current. n Wherein, the Fourier coefficient b n With the switching angle sequence α q 'As a parameter; for the switching angle sequence α q 'Optimization is performed to obtain the optimized switching angle sequence α' q According to α q The corresponding circuit is controlled by pulse width modulation to output a voltage waveform with specific harmonics filtered out. This invention obtains a specific switching angle sequence by establishing and solving a system of nonlinear equations. The output voltage waveform with specific harmonics filtered out is then modulated based on this switching angle sequence. This method can generate the desired frequency domain component and eliminate unwanted harmonics. It is also applicable to the design of multiple H-bridge units. At the same switching frequency, this method can output higher-order harmonics than other modulation methods, thus reducing switching losses. Furthermore, its excellent harmonic suppression performance saves hardware costs.

[Problem] To provide a polishing end point detection device and method, and a CMP device capable of accurately detecting a polishing end point when polishing a workpiece having a thin film thickness. [Solution] A polishing end point detection device (70) is provided with: a measurement unit (71) that, during polishing of a workpiece (W), radiates measurement light onto the workpiece (W), disperses reflected light from the workpiece (W), and acquires a spectral waveform indicating the relationship between the wavelength and reflectance of the reflected light; the reflectivity is the ratio of the intensity of the reflected light to the reference intensity of each wavelength component obtained in advance; and a detection unit (72) that calculates the film thickness of the thermal oxide film by applying Fourier analysis to the spectral waveform. The reference intensity is calculated by bringing a sample workpiece having substantially the same reflectance characteristic as a substrate of a workpiece (W) into contact with a polishing pad (5) in a state where a CMP slurry is interposed between the polishing pad (5) and the sample workpiece, and irradiating the sample workpiece with measurement light through an observation window (80) of the polishing pad (5) by a measurement unit (71). And the reflected light from the sample workpiece is split.

The invention provides a chronic lumbago surface electromyogram discrimination method and system based on a Fourier analysis neural network and a storage medium, and the method comprises the steps: firstly obtaining a data set which comprises a plurality of surface electromyogram signals and corresponding real labels; preprocessing the surface electromyogram signal to obtain a preprocessed surface electromyogram signal; inputting the preprocessed surface electromyogram signals into a constructed neural network based on Fourier analysis to obtain a prediction label of each surface electromyogram signal; constructing a loss function according to the real label and the predicted label, and training the neural network based on Fourier analysis to obtain a trained neural network based on Fourier analysis; and inputting a surface electromyogram signal to be detected into the trained neural network based on Fourier analysis to obtain a corresponding prediction label. According to the method, the neural network based on Fourier analysis is constructed and trained, the potential periodic features with discrimination are extracted, automatic discrimination of the abnormal modes in the chronic lumbago surface electromyogram signals is achieved, and therefore discrimination with higher robustness, higher generalization and higher efficiency is achieved.

The invention relates to the technical field of control panel signal processing, and provides a method for improving the anti-interference capability of a control panel, and the method comprises the steps: collecting the frequency characteristics of each motor control signal in the control panel, carrying out the Fourier analysis of the frequency characteristics to obtain a spectrogram, and dividing the control signals into a high-frequency signal group and a low-frequency signal group according to the spectrogram; time slot distribution is carried out on the control signals in the high-frequency signal group, the transmission period of the high-frequency signal group is divided into N time slots, and each control signal exclusively occupies one time slot; based on the frequency characteristics of the low-frequency signal group, constructing an orthogonal modulation basis vector, and mapping the control signal of the low-frequency signal group to the orthogonal modulation basis vector; and according to the time slot distribution scheme and the quadrature modulation basis vector, reconstructing the signal transmission time sequence of the control panel, so that the control signals of the high-frequency signal group and the low-frequency signal group do not interfere with each other. The technical problem that when multiple motors operate at the same time, control precision of a control panel is reduced due to mutual interference of control signals is solved.

A method for monitoring the quality of an ultrasonic weld, wherein the vibration behavior during the joining process with respect to an actual value of the vibration frequency and / or the vibration amplitude of at least one joining partner (10, 20) involved in the joining process and / or of a tool of an ultrasonic welding device (30) used in the joining process is detected by means of measurement with at least one measuring device (40) designed to quantify mechanical vibrations, the detected vibration behavior is analyzed by means of a Fourier analysis and compared with a predetermined target value as a reference value, wherein a frequency shift between an excitation frequency of the ultrasonic welding device (30) and the frequency measured at a measuring point during the joining process is detected and this is compared with a stored target frequency shift,to determine the degree of purity of the joining partners (10, 20) by means of the degree of frequency shift, wherein an eddy current sensor is used to quantify the mechanical vibrations during the joining process.