578 results about "Nonlinear distortion" patented technology

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention relates to the technical field of PCBs (printed circuit boards), in particular to an intelligent PCB detection and repair method, which comprises the following steps: S1, initializing module configuration: automatically identifying the type and structure information of a PCB; s2, a dynamic detection stage: collecting electrical parameters of the PCB, and generating fault position information; s3, circuit dynamic characteristic compensation: analyzing the nonlinear distortion characteristic of the circuit, and calculating and executing dynamic compensation; s4, an automatic repair stage: generating a repair scheme, including solder joint repair, line reconstruction or signal compensation; and S5, an intelligent recheck stage: performing comprehensive retest on the repaired PCB, verifying the performance of the repaired area, and generating a repair evaluation report. According to the invention, the repair precision and efficiency are improved, the whole repair process is intelligent and automatic, the risk of manual intervention is reduced, and the overall repair efficiency and the long-term reliability of the PCB circuit are improved.

The invention discloses a nonlinear equalization method, device and equipment and a storage medium, and relates to the technical field of communication, and the method comprises the steps: obtaining a floating point tap coefficient of an original equalizer, and carrying out the low-order quantization of the floating point tap coefficient, and obtaining an integer tap coefficient; constructing a target equalizer based on the integer tap coefficient; and compensating nonlinear distortion of a to-be-processed signal based on the target equalizer to obtain a recovered signal. Through the mode, the low-order quantization is performed on the tap coefficient of the equalizer, and the traditional floating-point number is converted into the low-order integer for representation, so that the storage space and the calculation complexity are remarkably reduced, the hardware implementation efficiency can be optimized and the power consumption can be reduced while the transmission performance is ensured.

The invention relates to a retiming circuit applied to an ultra-high-speed and high-precision DAC (Digital-to-Analog Converter), which comprises an alignment module, a cross point adjusting module, a coding module, a phase detection module and a digital module, the coding module is connected with the alignment module, the phase detection module is connected with the cross point adjusting module and the coding module, and the digital module is connected with the phase detection module and the alignment module. According to the circuit structure provided by the invention, the sampling clock can be accurately aligned to the center of a data eye pattern, so that the delay difference between a clock tree and a data path caused by process deviation and the like is effectively reduced, the high-frequency spurious suppression performance is improved by eliminating nonlinear distortion caused by time sequence errors, the SFDR is greatly improved, and compared with a traditional scheme, the SNR is effectively improved.

The invention provides a communication method and device, which can be applied to the technical field of wireless communication, and can enable a compensation model to be matched with a power amplifier (PA) in actual work, thereby accurately compensating nonlinear distortion of a signal caused by the PA, and not needing to carry out approximate mathematical modeling on the PA. The method comprises: a first device receiving a first signal and first information; wherein the first signal is a signal which is amplified by the first PA through adoption of the first gain, and the first information is used for indicating the first gain. And the first device determines a first compensation model according to the first signal and the first gain. Wherein the first compensation model is used for compensating non-linear distortion, and the non-linear distortion comprises the non-linear distortion on the signal in the process that the first PA adopts the first gain to execute amplification processing. For example, the first compensation model is a digital pre-distortion (DPD) model.

The invention discloses an electroencephalogram signal artifact removal method and an acquisition system. The method comprises the following steps: synchronously acquiring sensor data of a testee and each lead electroencephalogram signal by utilizing a unified trigger signal; performing timestamp alignment verification on the two types of synchronous data; a motion state quantitative index is determined, and if the motion state quantitative index does not exceed a preset motion threshold value, the collected electroencephalogram signals are output; if yes, an exception processing flow is triggered and comprises the steps that self-adaptive filtering and nonlinear compensation are sequentially executed on the electroencephalogram signals, static electroencephalogram data of the testee serve as reference in the self-adaptive filtering process, an NLMS filter with the step length dynamically adjusted is adopted, a motion artifact linear part and base noise are restrained, a self-adaptive filter is constructed based on the second-order Volterra series in the nonlinear compensation process, and the motion artifact linear part and the base noise are restrained; a kernel coefficient is optimized through an RLS algorithm, and nonlinear distortion is processed; and outputting the electroencephalogram signal after the exception processing. The method is suitable for non-linear and non-stationary motion artifact signals, signal synchronism and quality can be improved, and processing efficiency is considered.

The invention provides an image correction method and system based on a nonlinear distortion distribution elliptical fisheye lens, and a medium. The method comprises the following steps: establishing a nonlinear mixed distortion imaging model based on a mapping relation between image coordinates and a spherical direction; defining a distortion vector, and performing fitting processing on the distortion vector based on a two-dimensional B-spline function to obtain a distortion function; the method comprises the following steps: acquiring images in a five-surface three-dimensional angle calibration space based on an elliptical fisheye lens, analyzing lens imaging parameters, and generating parameter values of a distortion function; analyzing parameter values of the distortion function based on a nonlinear mixed distortion imaging model to generate calibration parameters, and remapping pixel points in the distorted image based on the calibration parameters; performing image reconstruction on the remapped distorted image to obtain a corrected image; improving the sampling density of a target area by constructing a nonlinear mixed distortion imaging model; the system adapts to complex monitoring environments such as galleries and entrances and exits; and spatial distortion is flexibly expressed through a B spline, so that the modeling capability is improved.

The invention discloses a method and a system for recovering time domain nonlinear distortion of an OFDM (Orthogonal Frequency Division Multiplexing) signal of satellite communication, which mainly solve the problem that the nonlinear distortion of the OFDM signal of the satellite communication is difficult to recover in the prior art. According to the scheme, the method comprises the following steps: acquiring a data set of satellite communication OFDM signal time domain nonlinear distortion recovery; constructing a deep learning network model composed of an optimized multi-layer one-dimensional convolutional neural network and a bidirectional long-short-term memory network module; inputting the acquired data set into a deep learning network model for training, verification and testing so as to recover a time domain distortion signal; and carrying out channel equalization and demodulation on the recovered time domain signal, completing demodulation from a modulation symbol to bit information, and realizing effective recovery and transmission of data. The method has good mean square error and bit error rate performance, the complexity of a network model can be reduced, signal distortion caused by nonlinear distortion can be effectively recovered, the precision and efficiency of signal recovery can be improved, and the method can be used for recovering nonlinear distortion signals in a satellite communication system.

The invention relates to the field of lithium battery intelligent monitoring, in particular to a low-temperature-resistant lithium battery BMS monitoring method and system based on cooperative sensing. The method comprises the following steps: acquiring surface temperature distribution, environment temperature and electrochemical parameters of the low-temperature tolerant lithium battery, and constructing a multi-source state characteristic matrix through space-time alignment and data fusion; applying a composite current excitation signal, and combining impedance analysis and spectrum analysis to extract impedance parameters, nonlinear distortion components and electrochemical stress factors to form a multi-dimensional feature vector; obtaining a state monitoring result by utilizing decision level fusion; through multi-sensor fusion and multi-dimensional feature fusion, the special internal state of the low-temperature tolerant lithium battery is comprehensively represented, early risk identification and early warning are carried out aiming at unique electrochemical behavior features of the low-temperature tolerant lithium battery, and compared with a common lithium battery monitoring method, the method has the advantages that the safety is high; and the accuracy, the robustness and the real-time performance of monitoring the state of the low-temperature tolerant lithium battery in the low-temperature environment are remarkably improved.

The invention relates to the technical field of digital image processing, in particular to an unmanned aerial vehicle image distortion correction and coordinate positioning compensation method, which comprises the following steps: collecting a large amount of unmanned aerial vehicle image data containing a damaged house, labeling the damaged house in the image, and generating a labeling file required by a YOLOv5 model; performing parameter calibration on the unmanned aerial vehicle lens to obtain a distortion coefficient of the lens, and constructing a nonlinear distortion correction model based on a lens parameter calibration result; establishing a dynamic affine transformation matrix in combination with the real-time flight attitude data of the unmanned aerial vehicle and the pixel coordinates of the detection frame; in a YOLOv5 detection stage, fusing feature maps with different resolutions, and fusing corrected coordinate data with a damaged house detection frame output by a YOLOv5 model; calculating coordinates of a center point of the damaged house according to the real-time latitude and longitude of the unmanned aerial vehicle; through dual optimization of image distortion correction and dynamic positioning compensation, the problem of coordinate misalignment caused by hardware limitation and unstable flight attitude in traditional unmanned aerial vehicle detection is solved.

The invention discloses a wide temperature range compensation method for resistive current of a lightning arrester, which belongs to the technical field of online monitoring of power equipment, and comprises the following steps: acquiring waveform data under a reference low-temperature working condition, and establishing an initial capacitive harmonic base; acquiring working condition data at any temperature in real time, performing harmonic decomposition, and analyzing to generate a nonlinear distortion feature vector; dynamically correcting the initial base by using the feature vector, and carrying out subtraction operation on the total current harmonic wave to obtain a final resistive current harmonic wave vector; and reconstructing an instantaneous resistive current waveform through inverse transformation and calculating a characteristic value. According to the technical scheme, the initial capacitive harmonic wave base is established, the nonlinear distortion feature vector is generated based on the harmonic distortion of the real-time working condition quantification temperature and valve plate nonlinear coupling, and dynamic feedback correction is conducted on the base, so that the real resistive current waveform in the wide temperature range can be accurately separated and reconstructed, and the accuracy of the real resistive current waveform in the wide temperature range is improved. And the accuracy and reliability of lightning arrester state evaluation are improved.

The invention relates to a narrowband minimum mean square error echo suppression method introducing a complex neural network, and belongs to the field of adaptive echo cancellation. An existing neural network method still has the problem of inaccurate priori knowledge modeling, and phase information in complex signals is not fully utilized. According to the method, a plurality of DNNs are adopted to carry out modeling and estimation on step length, loudspeaker nonlinear distortion and error signals respectively. And the adaptive capacity to an echo channel in a complex environment is improved by utilizing the efficient parameter learning capacity of a plurality of neural networks. According to the method, the phase information of complex data is fully utilized, the nonlinear distortion problem of the loudspeaker can be effectively suppressed, meanwhile, the small model parameter quantity is kept, efficient echo suppression is achieved, high practicability and hardware adaptability are achieved, and the method is suitable for various practical application scenes.

The invention discloses a differential closed-loop negative feedback amplification circuit based on JFET geminate transistors, a low-noise amplifier is used for measuring weak voltage signals, discrete JFET field-effect transistors are used for forming an input stage of the low-noise amplifier, noise interference is reduced, meanwhile, extremely high input impedance can be provided by using the characteristic that the grid current of the JFET field-effect transistors is basically zero, and the differential closed-loop negative feedback amplification circuit based on the JFET geminate transistors is obtained. Mirror current is provided for a pair of JFET field effect transistors in the low-noise amplifier module through a current mirror of the low-noise amplifier, a closed-loop feedback structure of the low-noise amplifier can save one path of input for the JFET field effect transistors, so that the amplifying circuit can realize dual-channel input, and a dual-channel input structure can enable an accessed signal to be a differential signal, so that common-mode interference is effectively inhibited, and the reliability of the amplifying circuit is improved. Overall closed-loop negative feedback can achieve high gain stability, reduce nonlinear distortion, increase input impedance, reduce output impedance and improve the performance of the amplifier, and solves the problem of precise amplification and measurement of weak voltage signals in the aviation electromagnetic field.

The invention discloses a high-frequency spark machine calibration method based on machining precision and stability control, and relates to the field of mechanical calibration, and the method comprises the steps: analyzing collected operation data, and building a data analysis model; the resonant frequency is dynamically adjusted based on the output frequency, and electromagnetic interference is eliminated through optical fiber transmission signals; an environment compensation mathematical model is constructed, and voltage deviation caused by environment change is automatically corrected; fundamental frequency and harmonic components are detected at the same time, and frequency deviation caused by nonlinear distortion is identified and compensated; a self-adaptive sensitivity adjusting mechanism is designed, a detection threshold value is dynamically adjusted based on the defect type and size, and sensitivity parameters of the high-frequency spark machine are automatically adjusted; the stability of the mechanical structure is predicted by simulating the assembly process; damping parameters of a mechanical structure are automatically adjusted, and the stability of high-frequency spark machine equipment is improved. The product quality and the production efficiency are guaranteed by improving the performance and the stability of the high-frequency spark machine.

The invention relates to the technical field of wireless communication, in particular to an OTA upgrading method and system for Bluetooth sound equipment. The method comprises the following steps: acquiring to-be-upgraded firmware data and currently played audio data, and acquiring power amplifier current feedback data of a sound speaker by sending a double-frequency detection signal containing 21kHz and 22kHz; acquiring equipment transmission capability confirmation data according to a silent response mode of the sound equipment to the preset handshake signal; and calculating a nonlinear distortion coefficient of the loudspeaker according to the intensity of the 1kHz difference frequency component in the power amplifier current feedback data, and obtaining real-time channel evaluation data based on current waveform deviation analysis. According to the method, the nonlinear distortion degree of the loudspeaker is accurately evaluated through the 1kHz difference frequency component generated by the 21kHz and 22kHz dual-frequency detection signals, so that the reliability of data transmission is more accurately predicted.

An apparatus and method are provided for digital predistortion of an electrical signal to pre-compensate for nonlinear distortions in a nonlinear channel (e.g., a nonlinear channel including a high-power amplifier). The digital predistortion processor includes a nonlinear filter. Filter coefficients are determined using a modified input electrical signal having multiple simultaneous tones, using an iterative process which adapts the modified input electrical signal to reduce levels of intermodulation distortions in a modified output electrical signal.

The invention is suitable for the technical field of semiconductor testing, and provides a data acquisition method and device based on a DDIC chip, and testing equipment, and the data acquisition method comprises the steps: receiving a test pattern, controlling the DDIC chip to output a corresponding gray scale voltage signal, and achieving the comprehensive testing of the response capability of the chip in a full gray scale range; secondly, a target acquisition link composed of functional units including impedance conversion, single-ended to differential conversion, programmable gain amplification, filtering, analog-to-digital conversion and the like is utilized, so that the signal driving capability and the anti-interference capability are effectively improved, meanwhile, high-frequency noise and nonlinear distortion are reduced, and the basic quality of sampled data is guaranteed; on the basis, sampling optimization processing is carried out on the sampling data based on the FPGA unit, and the data stability is improved. According to the scheme, through high-precision transmission of the signal link, the data acquisition precision of the DDIC chip is improved, and then the technical requirements of high-precision DDIC chip testing are met.

Methods for sending and receiving capability information and / or configuration information regarding digital post-distortion (DPoD) capabilities and / or use. A method, in a first device, comprises sending, to a second device, capability information indicating the first device's ability to perform digital post-distortion (DPoD) processing to reduce non-linear distortion in signals received by the first device. A method, in a second device, comprises receiving, from a first device, capability information indicating the first device's ability to perform digital post-distortion (DPoD) processing to reduce non-linear distortion in signals received by the first device.

The invention relates to the technical field of surface mounting, and discloses an SMT (Surface Mount Technology)-based patch vision correction method, which comprises the following steps: S1, a calibration stage: constructing a double-coordinate system mapping model based on a PCB (Printed Circuit Board) plane, and establishing a nonlinear distortion compensation matrix according to the patch thickness; s2, a pickup stage: a CCD shooting camera is arranged at the top of the suction nozzle, a top CCD is triggered to shoot when the suction nozzle picks up an element, and pin coplanarity data is extracted; s3, a positioning stage: setting a reference point at the top of the PCB, scanning the PCB reference point through a CCD, and calculating a deviation between an actual position and a theoretical coordinate by using an algorithm processor; and S4, compensation execution: the motion shaft system dynamically adjusts the mounting path according to the deviation vector. The visual correction method based on SMT pasting has the advantages of accurate pasting and the like, and solves the problems of pasting position offset, low efficiency and unstable precision caused by factors such as vibration of an element feeder, mechanical transmission errors and thermal deformation of a PCB (Printed Circuit Board) due to dependence on manual calibration in the existing SMT pasting process.

The invention relates to the technical field of signal correction, in particular to a nonlinear distortion correction method for a vibration monitoring signal, and provides the following scheme: carrying out broadening and sparse reconstruction on a vibration signal through dispersion Fourier transform and compressed sensing, and extracting a high-frequency local structure; on the basis of phase-space reconstruction and a Lyapunov exponent, nonlinear distortion segments are identified; further performing orbit guiding modeling and degradation path reasoning on the orbit cluster corresponding to the segment, and selecting a reference orbit matched with the structure from the residual linear segments; and constructing an affine mapping relation between orbits and back-projecting the affine mapping relation to a time domain to generate a correction signal. According to the invention, high-precision identification and low-error correction of millisecond-level local nonlinear distortion are realized, and the stability and accuracy of vibration signal analysis are improved.

The invention relates to the technical field of aluminum alloy forming processes, and discloses an intelligent optimization method of an aluminum alloy round aluminum rod forming process. The method comprises the following steps: acquiring process parameter monitoring data of smelting, casting and rolling stages, wherein the process parameter monitoring data comprises temperature gradient, pressure fluctuation value and alloy component real-time variation; based on the time sequence relevance of the technological parameter monitoring data of the smelting stage and the casting stage, the technological parameter transmission delay amount between the two stages is calculated, and the parameter fluctuation compensation factor of the casting stage is determined accordingly. And determining the energy interference intensity of each process stage in the corresponding frequency domain according to the temperature gradient difference value, the pressure fluctuation change rate and the alloy component offset of the adjacent process stages in the short-time window. And generating a process nonlinear distortion probability based on the energy interference intensity distribution of all adjacent process stages. And the pressure control reference value in the rolling stage is dynamically adjusted according to the process nonlinear distortion probability. By means of the method, intelligent optimization of the aluminum alloy round aluminum rod forming process is achieved.

The invention relates to the technical field of audio processing, and discloses an audio output control method, device and equipment and a storage medium, and the method comprises the steps: detecting an input voltage signal and collecting an audio input signal through an MCU control unit, obtaining a voltage parameter matrix and an audio parameter matrix, and combining the voltage parameter matrix and the audio parameter matrix to form a mixed feature matrix; inputting the mixed feature matrix into a deep neural network for feature extraction to obtain an audio feature space; constructing a cross attention model, calculating an association weight value among the audio parameters, and generating an audio curve switching control sequence; switching a control sequence based on an audio curve, dynamically adjusting the voltage of the power amplifier through a feedback controller, and collecting working state data of the power amplifier; and performing nonlinear distortion compensation and noise suppression processing on the working state data of the power amplifier to generate an audio output quality parameter, thereby effectively solving the problem of unstable audio output under different power supply conditions, and realizing intelligentization and precision of audio output control.

Embodiments relate to systems and methods for compensating nonlinear distortions. The system receives a signal corresponding to an input sound pressure which is detected by a capacitive MEMS microphone. The capacitive MEMS microphone includes an active capacitance and a parasitic capacitance. The system determines a nonlinear relationship between the signal and the input sound pressure; and determines, based on the signal, an input parameter associated with the active capacitance and the parasitic capacitance. The system further determines an output signal based on the input parameter and the output signal and the input sound pressure have a linear relationship. The system compensates the signal based on the determined output signal and outputs the compensated signal as an output so that the output has the linear relationship with the input sound pressure.

The invention discloses an optical fiber current transformer phase demodulation method and system, a terminal and a storage medium, and the method comprises the steps: obtaining a light intensity signal outputted by an all-optical fiber current transformer, a frequency doubling carrier signal and a frequency doubling carrier signal, converting the light intensity signal into an output signal, and carrying out the signal internal modulation, obtaining a first tangent signal and a second tangent signal; performing ellipse fitting on discrete sampling points of the first tangent signal and the second tangent signal to obtain a first initial ellipse parameter set; inputting the first tangent signal and the second tangent signal into the trained neural network for elliptic surface fitting to obtain a second initial elliptic parameter set; and comparing the first initial ellipse parameter with the second initial ellipse parameter to obtain an optimal ellipse parameter, and calculating and processing by combining the optimal ellipse parameter to obtain a correct demodulation signal. According to the invention, the nonlinear distortion of the signal can be effectively suppressed, the demodulation linearity is good, the accuracy is high, and the sensing precision of the all-fiber current transformer is improved.

The invention relates to the technical field of radio frequency signal processing, and discloses a digital filtering repair method and system for signal distortion, and the method comprises the steps: obtaining a frequency domain amplitude-frequency response and a phase response; constructing a phase compensation amount by adopting piecewise polynomial fitting and a phase inversion mechanism; a complex number logarithm domain mapping mechanism is adopted to execute composite frequency response inversion; constructing a switchable hybrid digital filter with an amplitude path and a phase path coupled in parallel; multi-band adaptive scheduling is executed; and outputting the radio frequency baseband signal stream. The technical problems that in the prior art, frequency response nonlinear distortion in a broadband range cannot be dealt with by adopting a fixed template or a single-path filter, and particularly, a high-precision and low-delay dynamic compensation effect cannot be realized in a scene that multi-band coupling interference exists in a radio frequency ADC channel with the bandwidth exceeding 800MHz are solved. Due to the fact that the switchable hybrid digital filter is constructed, accurate modeling and flexible recovery of distortion characteristics in broadband signals are achieved.

The invention discloses a three-dimensional geometric reconstruction camera calibration method and system, and relates to the technical field of three-dimensional geometric reconstruction, and the method comprises the steps: S1, image collection; s2, automatic calibration point selection; s3, estimating camera parameters; s4, distortion correction is carried out; and S5, performing three-dimensional reconstruction verification. According to the three-dimensional geometric reconstruction camera calibration method and system, a calibration point does not need to be selected manually, the calibration process is simplified, the complexity and time cost of the calibration process are reduced, a high-precision calibration result can be obtained without shooting a plurality of plane images and carrying out a plurality of optimization iterations, and the calibration efficiency is improved. The calculation amount and the time cost are further reduced, and camera calibration can be quickly and accurately realized; in addition, nonlinear distortion of a camera lens is fully considered, the calibration precision is further improved, and the method is particularly suitable for the situation that a wide-angle lens is used or an image contains large distortion.

Embodiments relate to systems and methods for compensating nonlinear distortions. The system receives a signal corresponding to an input sound pressure which is detected by a capacitive MEMS microphone. The capacitive MEMS microphone includes an active capacitance and a parasitic capacitance. The system determines a nonlinear relationship between the signal and the input sound pressure; and determines, based on the signal, an input parameter associated with the active capacitance and the parasitic capacitance. The system further determines an output signal based on the input parameter and the output signal and the input sound pressure have a linear relationship. The system compensates the signal based on the determined output signal and outputs the compensated signal as an output so that the output has the linear relationship with the input sound pressure.

The invention discloses a preprocessing method for a digital baseband signal of a receiver, which comprises the following steps of: quantifying the sparse degree of the signal by selecting a proper sparsity measurement index, constructing an optimization problem based on the selected sparsity measurement index, and then minimizing the sparsity index of the signal in a transform domain, namely searching a group of compensation parameters. The sparsity of the compensated signal in the transform domain is restored to the level close to that of the original signal, and then the established optimization problem is solved by using a numerical optimization algorithm to find the optimal compensation parameter. According to the method, the sparsity of the signal can be effectively recovered, so that the nonlinear distortion at the front end of the receiver is compensated, and the signal quality and the system performance are improved.

The invention provides a phase generated carrier demodulation method based on two-parameter estimation. The method comprises the following steps of: firstly, realizing estimation of a C value by extracting an amplitude ratio of a carrier frequency multiplication component in an interference signal frequency spectrum and combining a Bessel function characteristic; then, carrying out operation processing by utilizing a first frequency multiplication signal and a second frequency multiplication signal to extract carrier phase delay theta c; and finally, eliminating the influence through dynamic phase compensation. According to the demodulation method provided by the invention, the nonlinear drift of the modulation depth parameter C and the synchronous estimation and compensation of the carrier phase disturbance signal theta c can be realized, the cross interference error in the traditional demodulation system is effectively inhibited, the phase demodulation robustness is remarkably improved, and the harmonic nonlinear distortion is effectively inhibited.

The invention provides a method for automatically determining the content of main elements in lithium battery black powder, and belongs to the technical field of lithium batteries. Characteristic spectral line intensity is collected by adopting an inductively coupled plasma emission spectrometer, background signals are deducted through wavelet multi-resolution decomposition, and the content of the main elements in the lithium battery black powder is obtained. Spectral overlapping peaks are separated through Fourier transform, an internal standard element is used for correcting a matrix effect, signal fluctuation introduced by pulse of a peristaltic pump is eliminated by adopting Kalman filtering, and relative intensity subjected to filtering smoothing is input into a multi-scale concentration calibration model with a layered soft maximum value classification layer; according to the model, interval affiliation probability distribution is output through a coarse-grained classifier, a fine-grained classifier is selected to carry out local concentration prediction and weighted fusion is carried out to obtain a concentration prediction value, and quality control standard sample monitoring and an instrument recalibration mechanism are combined; the technical problem that the measurement precision is reduced due to nonlinear distortion of a calibration curve when the multi-element concentration in the lithium battery black powder crosses a wide concentration range is solved.