9 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.

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.

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 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.

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

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.

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.