18 results about "Time domain signal processing" patented technology

This application discloses a portable online electrochemical impedance spectroscopy measurement system and method for lithium-ion batteries, relating to the field of lithium-ion battery technology. The system includes: a power supply system for powering a power transmission system and an online measurement system, connected in parallel with a charger connected to the battery pack to achieve synchronous charging and impedance measurement; a power transmission system for converting direct current into a step function current, which is superimposed on the DC charging current and injected into the battery pack as an excitation signal; a control system for adjusting the frequency of the step function current using pulse width modulation technology; a measurement circuit module for acquiring the current and voltage signals of the battery pack; and a data analysis module for processing the time-domain signal using wavelet transform to calculate the electrochemical impedance spectrum. This application achieves low-cost, portable online measurement, enabling monitoring of the battery impedance spectrum during charging and providing support for safety early warning.

The invention relates to the technical field of equipment detection, in particular to an insulating oil aging marker detection system and method and a storage medium, and the system is characterized in that laser generated by a laser device is split into a first light beam and a second light beam through a spectroscope, and the first light beam excites a photoconductive antenna to generate terahertz pulses; the terahertz pulse enters the first reflection assembly, and the first reflection assembly reflects the terahertz pulse to a sample in the sample pool; the acquisition assembly acquires a time domain signal after mixing the terahertz pulse absorbed by the sample and the second light beam; and the processing assembly performs fitting according to the terahertz pulse absorbed by the sample and the time domain signal after the second light beam is mixed to obtain a terahertz absorption spectrum, and analyzes the insulating oil aging marker of the sample according to the terahertz absorption spectrum. Therefore, the problems that a detection mode in the related technology is difficult to meet on-site rapid and real-time intelligent monitoring requirements, the detection period is long and the like are solved.

To address the insufficient generalization ability of existing sound source localization techniques, this invention provides a sound source localization method and a training method for a neural network model. The sound source localization method of this invention includes: obtaining a reverberation field time-domain signal; processing the reverberation field time-domain signal into a probability map to form a reverberation field dataset; inputting the reverberation field dataset into a neural network model to obtain the sound source localization result output by the neural network model; the neural network model includes sequentially arranged modules: a CNN module, a Transformer module, and an FFT module. The technical solution of this invention can be widely applied in the field of sound source localization technology.

This application relates to the field of handheld laser rangefinder technology, and in particular to a handheld laser rangefinder and its testing method. The handheld laser rangefinder body includes a shell, a dual-wavelength laser emitting module, an ambient light intensity sensor, an FPGA time-domain signal processing unit, a temperature compensation system, an LCD screen, and control buttons. The dual-wavelength laser emitting module includes a laser and a light receiver disposed at the end of the shell, and an 808nm / 905nm dual-band laser diode disposed inside the shell. By incorporating the dual-wavelength laser emitting module, the ambient light intensity sensor, the FPGA time-domain signal processing unit, and the temperature compensation system, the handheld laser rangefinder can switch the main wavelength in real time via the ambient light sensor. The switching logic is as follows: when the ambient light sensor detects an illuminance greater than 5000 lux, the 905nm band is automatically activated; when the illuminance is less than or equal to 5000 lux, the 808nm band is used, thereby reducing sunlight interference.

The present invention discloses a method for extracting weak sound features from a moving sound source. The method comprises the following steps: step 1, processing a time domain signal of a moving sound source received by a receiver to obtain energy time history data of each frequency / frequency band; step 2, selecting one frequency / frequency band, using a filtering algorithm to remove pulse interference from the energy time history data of the frequency / frequency band, and performing a sliding average process; step 3, performing an N-order Fourier series decomposition on the energy time history data of the frequency / frequency band; step 4, retaining the first M orders of the Fourier series amplitude, setting the amplitudes of the remaining orders to zero, and then performing an N-order inverse Fourier transform; and step 5, removing the fixed background noise component according to a criterion for removing the fixed background noise component from the received signal, and obtaining the maximum signal energy at the positive horizontal moment of the frequency / frequency band. The present invention can remove the fixed background noise component and pulse interference from the received signal, improve the signal-to-noise ratio of the received signal, and realize weak sound feature extraction from the moving sound source.

This invention belongs to the field of ultrasonic scanning imaging technology and provides a method and system for ultrasonic scanning imaging of composite materials based on correlation analysis. First, a set of ultrasonic scanning signals from a defect-free region of the test piece is selected as a reference, and the autocorrelation function of the reference is determined. Then, based on the autocorrelation function of the reference, a standard autocorrelation function of the ultrasonic scanning signal is obtained through multiple iterations of optimization and noise reduction. Based on the standard autocorrelation function, the difference between the autocorrelation function of each ultrasonic scanning signal to be tested and the standard autocorrelation function is determined. Finally, an ultrasonic scanning image is plotted based on the difference between the autocorrelation function and the standard autocorrelation function. By using signal autocorrelation analysis to replace time-domain signal processing in the ultrasonic scanning imaging process, the problem of signal time-domain offset caused by changes in coupling distance is avoided. Only a small amount of reference signal needs to be collected in the defect-free region to establish a detection reference, eliminating the need for manually setting a detection gate and significantly reducing reliance on experience.

The invention discloses a multi-band fusion demodulation spectrum calculation method based on multi-feature joint weighting. The method comprises the following steps: 1, generating N band-pass filter banks which can completely cover all available bands of a signal and have the same bandwidth and mutually overlapped passbands; 2, processing the time domain signal into a band-pass signal xn (t) by using a filter bank, and calculating a demodulation spectrum Dn (f) of the xn (t) by using square detection; 3, calculating skewness Sn and kurtosis Kn of the demodulation spectrum Dn (f) of each frequency band, and determining a fusion weighting coefficient Wn of each frequency band according to the skewness Sn and kurtosis Kn; and step 4, calculating an adaptive fusion demodulation spectrum D (f) according to the weighting coefficient. The method can effectively adapt to the optimal demodulation frequency band difference caused by the marine environment and the target type, greatly improves the demodulation spectrum detection and identification capability of the suspicious target under the condition of low signal-to-noise ratio, and is good in adaptability, simple in processing method and high in reliability.

The invention discloses an EEG-fNIRS visual information decoding method, which comprises the following steps of: synchronously acquiring an EEG time domain signal and an fNIRS time domain signal generated when a subject watches a visual stimulation image, and processing to obtain an EEG time-frequency spectrogram and an fNIRS time-frequency spectrogram; respectively inputting the EEG time-frequency spectrogram and the fNIRS time-frequency spectrogram into a Transform encoder, and respectively generating an EEG feature embedding vector and an fNIRS feature embedding vector; jointly inputting the EEG feature embedding vector and the fNIRS feature embedding vector into a multi-modal attention fusion module to generate a mixed embedding vector; and reconstructing the hybrid embedded vector into a final image by adopting a two-stage decoding strategy. According to the method, the high-quality visual image with accurate semantics and rich details can be generated from the brain signal.

The invention discloses a radar time domain signal processing method based on CEEMDAN-ICA, and the method comprises the steps: carrying out the decomposition of a received radar time domain signal through employing a CEEMDAN algorithm, obtaining IMF components with frequencies from high to low, calculating the fuzzy entropy coefficient of each order of IMF components, solving the mean value of the IMF components, selecting an IMF component larger than the mean value of fuzzy entropy according to the fuzzy entropy coefficient, determining the IMF component as a noise component layer, and carrying out the recognition of the noise component layer. The radar time domain signals and original signals are simultaneously used as input of a FastICA algorithm, and effective signals in the radar time domain signals are separated. According to the scheme, a modal decomposition method is utilized, priori knowledge and a fixed primary function are not needed, the original signal can be processed only by adjusting parameters, and noise can be effectively suppressed, so that the signal-to-noise ratio of the radar time domain signal is improved, the signal can be adaptively subjected to modal decomposition, and the robustness of the radar time domain signal is improved. Noise can be well suppressed while radar time-domain signal characteristics can be reserved as far as possible, and meanwhile, the accuracy of radar time-domain signal sorting is improved.

The invention provides a high-order QAM (Quadrature Amplitude Modulation) optical general filtering multicarrier transmission method based on odd subcarrier auxiliary channel estimation, which comprises the following steps: a sending end maps a binary bit stream into a high-order QAM symbol, and transmits a sending signal through an optical fiber transmission channel after inverse fast Fourier transform and sub-carrier band general filtering; a receiving end performs time domain signal processing on the sending signal, separates an even-numbered subcarrier receiving signal and an odd-numbered subcarrier receiving signal through fast Fourier transform, and performs matched filtering on the even-numbered subcarrier receiving signal and the odd-numbered subcarrier receiving signal; performing channel frequency response estimation by using the matched and filtered odd subcarrier receiving signal to assist the matched and filtered even subcarrier receiving signal; and performing zero-forcing equalization on the even subcarrier receiving signal after matched filtering by using channel frequency response estimation to obtain an equalized even subcarrier sending signal, and performing de-mapping to obtain a recovered binary bit stream. According to the method, the defects of traditional LS channel estimation are compensated, and the accuracy of channel estimation is effectively improved under the condition that extra system resource overhead is not increased.

TITLE: Method and System for Structural Diagnosis of Concrete Railway Sleepers This structural diagnostic method comprises four steps: an application step, in which a mechanical stress is applied by impact to a concrete railway sleeper (2, 3) to be diagnosed; a detection step, in which a vibration generated by the mechanical stress and propagating through the sleeper being diagnosed is detected on the surface of the sleeper and transformed into a vibrational time-domain signal; a processing step, in which the vibrational time-domain signal is electronically processed to obtain a frequency spectrum; and an analysis step, in which the frequency spectrum is compared to a reference to deduce a structural damage characterization of the sleeper being diagnosed. Figure for the abstract: Figure 1

This invention provides a method, device, and storage medium for human presence detection based on Doppler radar. The method includes: preprocessing intermediate frequency signals sampled within the sensing range; determining whether a moving object exists in the current space based on human motion detection signals; performing time-domain signal processing and analysis on micro-motion and respiratory frequency range signals to determine whether human micro-motion or respiratory frequency exists in the current space; converting the preprocessed time-domain signal into a frequency-domain signal, and extracting the human respiratory frequency signal through processing and spectral analysis of the frequency-domain signal to determine whether a human body exists in the current space; and determining the presence status of a human body within the current sensing range based on human motion detection, time-domain respiratory signal detection, and frequency-domain respiratory signal detection. This invention can effectively filter interference signals and improve the accuracy and sensitivity of human presence detection.

The invention relates to the technical field of computer architecture, in particular to a mathematical operation system which comprises an input preprocessing module, a reconfigurable calculation engine, a dynamic precision controller and an output interface. By deconstructing a technical feature set of target patent claims, legal compliance is realized by adopting a feature omission (deleting unnecessary error feedback units) and parameter breakthrough (setting step length gt; 0.5) strategy. Frequency domain transformation is innovatively applied to the field of time domain signal processing, and a recursive decomposition architecture is replaced by parallel butterfly operation, so that the throughput is improved by three times while the memory occupation is reduced by 40%.

A signal processing method of processing frequency domain signal data is described. The signal processing method includes at least the steps of applying, by the signal processing circuit, a first window function and a second window function to frequency domain signal data, thereby obtaining first modified signal data and second modified signal data, wherein the second window function is different from the first window function. The modified signal data can then be transformed into time domain. The signal processing circuit or other circuitry, such as a visualization circuit, may then generate joint visualization data based on the first transformed signal data and based on the second transformed signal data, wherein the joint visualization data comprises information on both the first transformed signal data and the second transformed signal data. Further, a measurement instrument is described.

The invention provides an analog-to-digital converter based on time domain signal processing, and the circuit of the converter comprises two conversion circuits containing decision devices, and also comprises a time schedule controller and a data serial-to-parallel conversion circuit. Each conversion circuit comprises a sampling circuit, a converter, a selector and a pulse shaper which are sequentially arranged in a signal processing direction; when the circuit converts a voltage signal input by a sampling circuit into N-bit quantized output, input signals of the circuit are a system clock CKS, a digital trigger signal CKSA and analog input voltage signals VCOM, VIN2 and VIN1, the VIN1 and the VIN2 are differential voltage signals to be sampled and converted, and the VCOM is analog reference voltage; the output signal comprises a sampling completion signal RDY and a quantization output code DOUTlt; n-1: 0gt; ; the invention has the advantages of wide power supply voltage range, difficulty in process influence and the like.

For each frame, an n-th channel compensated decoded sound signal ˜X′n is obtained that is a signal obtained by compensating a high frequency of an n-th channel purified decoded sound signal ˜Xn obtained by performing signal processing in a time domain on an n-th channel decoded sound signal {circumflex over ( )}Xn (n is each integer of 1 or more and N or less) that is a decoded sound signal of each channel of stereo obtained by decoding a stereo code CS. At this time, for the each frame with respect to the each channel, an n-th channel high-frequency compensation gain ρn that is a value for bringing high-frequency energy of the n-th channel compensated decoded sound signal ˜X′n close to high-frequency energy of the n-th channel decoded sound signal {circumflex over ( )}Xn is obtained, and for the each frame with respect to the each channel, a signal obtained by adding the n-th channel purified decoded sound signal ˜Xn and a signal obtained by multiplying a high-frequency component of the n-th channel decoded sound signal {circumflex over ( )}Xn by the n-th channel high-frequency compensation gain ρn is obtained and output as the n-th channel compensated decoded sound signal.

The invention relates to the technical field of blade state monitoring of wind power equipment, in particular to a wind turbine generator time domain signal processing method and device and a storage medium, and the method comprises the steps: obtaining originally collected time domain signals and corresponding sampling interval time; the method comprises the following steps: inputting an originally collected time domain signal into a first-order low-pass filter, setting the length of a sliding window of the first-order low-pass filter, obtaining an output corresponding to each sliding window through low-pass filtering processing, and taking the output as a mean value of the time domain signal in the corresponding sliding window. The method is low in resource occupation, high in calculation efficiency and easy to implement.

The invention relates to the technical field of signal processing, and particularly provides a perovskite X-ray image acquisition system and method based on time domain signal processing, and the system comprises a radiation source module, a detector module, an analog front end module, an ADC module, an FPGA module, a high-speed interface module and an upper computer module. The detector module is used for carrying out charge collection and integration on photons to obtain integral node voltage in pixels, the analog front-end module is used for sampling the integral node voltage in the pixels to obtain multi-channel analog differential voltage, and the ADC module is used for carrying out synchronous sampling quantization on the multi-channel analog differential voltage to obtain a pixel value sequence and a synchronous marking signal. The FPGA module is used for carrying out time domain signal processing to obtain image frames and metadata, the high-speed interface module is used for carrying out packaging to obtain an Ethernet frame packet, and the upper computer module is used for carrying out unpacking display on the Ethernet frame packet to obtain a control signal. According to the invention, the imaging quality and precision are improved by adding the FPGA module.