- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - A Two-frequency Subtraction Method to Improve Spectral Peak Identifications
摘要： We discuss a two-frequency subtraction technique to reduce the energy leakage in a Fourier spectrum. In our method, frequency components are determined by finding the periodogram over an interval such that the two frequencies will not interfere with each other. Such a method allows the subtraction of the two main frequency components more accurately from the original signal. The energy leakage from the main components is minimized to allow identification and more accurate determination of weaker components. Statistical error from the subtraction technique can be several times smaller than the FFT method. We show that the subtraction method is relatively robust for signals with varying amplitude or frequency.
关键词： time-frequency analysis,Fourier transform,spectrum estimation,spectral leakage
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) - Houston, TX (2018.5.14-2018.5.17)] 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) - Multi-core cable fault diagnosis using cluster time-frequency domain reflectometry
摘要： Guaranteeing the integrity and functionality of the control and instrumentation (C&I) cable system is essential in ensuring safe nuclear power plant (NPP) operation. When a fault occurs in a multi-core cable, it not only affects the signals of faulty lines but in fact, disturbs the rest as well due to crosstalk and noise interference. Therefore, this results in C&I signal errors in NPP operation and further leads to a rise in concern regarding the NPP operation. Thus, it is necessary for diagnostic technologies of multi-core C&I cables to classify the faulty line and detect the fault to assure the safety and reliability of NPP operation. We propose a diagnostic method that detects the fault location and faulty line in multi-core C&I cable using a clustering algorithm based on TFDR results. The faulty line detection clustering algorithm uses TFDR cross-correlation and phase synchrony results as input feature data altogether which can detect the faulty line and identify the fault point successfully. The proposed clustering algorithm is verified by experiments with two possible fault scenarios in NPP operation.
关键词： fault diagnosis,reflectometry,control and instrumentation cable,K-means clustering,crosstalk,time-frequency analysis
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP) - Vancouver, BC (2018.8.29-2018.8.31)] 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP) - An Adaptive Bandpass Filter Based on Temporal Spectrogram Analysis for Photoplethysmography Imaging
摘要： Photoplethysmography Imaging (PPGI) in the sense of remote vital sign measurement via camera has attracted high interest in recent years. The non-contact measurement principle allows the use in many health monitoring applications, like monitoring of newborns. Beyond that, there are interesting areas of application in the multimedia sector, such as measuring the reaction to multimedia content or heart rate based liveness detection for multimedia security. The derived signal of a PPGI algorithm is often referred as blood volume pulse signal (BVP). The signal corresponds to the optical signal of blood volume changes in the upper skin layers. Most current approaches use peak detection in frequency spectrum to estimate heart rate from BVP signals. However, we focus on heart rate computation based on beat-to-beat peak detection in time domain. In this paper, we present a method for adaptive bandpass filtering for PPGI based on temporal spectrogram analysis of the BVP signal with a sliding time window. The main goal of this new method is to further improve accuracy of beat-to-beat peak detection in time domain. The approach exploits the analysis of main frequency components of the BVP signal over time, to build a bandpass filter with adaptive cutoff frequencies in order to filter noise and interference. So far, state-of-the-art approaches have usually used fixed cut-off frequencies in the physiologically possible range of heart rate. The novelty of the proposed method lies in its simple but effective solution to reduce the influence of noise and interference in the PPGI signal to improve peak detection for heart rate estimation. We show the improvements applying the adaptive bandpass filter technique to four basic algorithmic approaches of PPGI, namely ICA, Chrominance, POS and 2SR and comparing against current state-of-the-art peak detection approaches. For the evaluation we used a database with videos of 26 subjects in 4 different scenarios, each lasting two minutes.
关键词： Photoplethysmography Imaging,time frequency analysis,signal processing,user reaction,peak detection,remote heart rate estimation,adaptive bandpass filtering
更新于2025-09-23 15:22:29
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An amplitude weak component detection technique based on normalized time-frequency coefficients and multi-synchrosqueezing operation
摘要： In the areas of measurement, instrumentation and sensing across science and engineering, the recorded signal is typically manifested as a strong non-stationary characteristic and the amplitude of each component is varied among each other. An effective signal processing algorithm which could clearly reflect the fast varying frequency fluctuations of all components is necessary to be proposed. As a recently proposed time-frequency analysis algorithm, Multi-synchrosqueezing transform owns the ability to squeeze the diffused time-frequency (TF) coefficients into the correct instantaneous frequency trajectory position in a TF plane iteratively. However, the amplitude related time-frequency representation result still makes it difficult to detect the fast varying instantaneous frequency for the amplitude weak component contained in a multi-component signal. To address this issue, this study employs a combined normalized time-frequency coefficients and multi-synchrosqueezing operation technique to make a complete exhibition of the complex TF structure of a multi-component signal with various amplitude weak components. In the proposed method, the amplitude related TF coefficients are all normalized as a constant value and only the reassigned TF positions after conducting the multi-synchrosqueezing operation multiple times are retained. By exploiting the proposed method on multi-component signals with amplitude weak components, the TF structure for all components can be clearly observed. The effectiveness of the proposed method is evaluated both on a set of simulated data and a set of experimental rubbing fault signal, the implementation results are sufficient to demonstrate the superiority of the proposed method.
关键词： Time-frequency analysis,Multi-synchrosqueezing operation,Multi-synchrosqueezing transform,Non-stationary signal,Amplitude weak component detection
更新于2025-09-19 17:15:36
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[IEEE 2018 5th International Conference on Information Science and Control Engineering (ICISCE) - Zhengzhou, China (2018.7.20-2018.7.22)] 2018 5th International Conference on Information Science and Control Engineering (ICISCE) - A Portable 24GHz Doppler Radar System for Distant Human Vital Sign Monitoring
摘要： Vital sign detection using Doppler radar can be potentially applied in health care and home monitoring. While most of developed Doppler radars are designed in laboratory environments, this paper introduces a portable 24 GHz Doppler radar using commercial modules at low cost. The Doppler radar system adopts the commercially available 24GHz transceiver module to obtain analog quadrature signals, the signals are digitalized using analog-to-digital conversion in microcontroller, then sent to laptop or mobile phone via a series to WIFI module. All the modules are implemented on a printed circuit board to achieve the small size. Experiments validate that the Doppler radar can sense human respiration and heartbeat rates successfully using time frequency based signal processing algorithms.
关键词： vital sign detection,Doppler radar,time frequency analysis,heartbeat and respiration
更新于2025-09-19 17:15:36
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Study on a Multi-channel Switchable and Environment Self-adaptive Ultrasonic Sensor in an Erbium-doped Fiber Ring Laser
摘要： The usefulness of the information contained in biomedical data relies heavily on the reliability and accuracy of the methods used for its extraction. The conventional assumptions of stationarity and autonomicity break down in the case of living systems because they are thermodynamically open, and thus constantly interacting with their environments. This leads to an inherent time-variability and results in highly nonlinear, time-dependent dynamics. The aim of signal analysis usually is to gain insight into the behavior of the system from which the signal originated. Here, a range of signal analysis methods is presented and applied to extract information about time-varying oscillatory modes and their interactions. Methods are discussed for the characterization of signals and their underlying nonautonomous dynamics, including time-frequency analysis, decomposition, coherence analysis and dynamical Bayesian inference to study interactions and coupling functions. They are illustrated by being applied to cardiovascular and EEG data. The recent introduction of chronotaxic systems provides a theoretical framework within which dynamical systems can have amplitudes and frequencies which are time-varying, yet remain stable, matching well the characteristics of life. We demonstrate that, when applied in the context of chronotaxic systems, the methods presented facilitate the accurate extraction of the system dynamics over many scales of time and space.
关键词： phase coherence,coupling function,Biomedical signal analysis,dynamical Bayesian inference,wavelet bispectrum,cardiovascular system,time-frequency analysis,brain dynamics,time-dependent dynamics
更新于2025-09-19 17:13:59
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - High Power Terahertz Source Based on Planar Antenna Integrated Vacuum Photodiode
摘要： The usefulness of the information contained in biomedical data relies heavily on the reliability and accuracy of the methods used for its extraction. The conventional assumptions of stationarity and autonomicity break down in the case of living systems because they are thermodynamically open, and thus constantly interacting with their environments. This leads to an inherent time-variability and results in highly nonlinear, time-dependent dynamics. The aim of signal analysis usually is to gain insight into the behavior of the system from which the signal originated. Here, a range of signal analysis methods is presented and applied to extract information about time-varying oscillatory modes and their interactions. Methods are discussed for the characterization of signals and their underlying nonautonomous dynamics, including time-frequency analysis, decomposition, coherence analysis and dynamical Bayesian inference to study interactions and coupling functions. They are illustrated by being applied to cardiovascular and EEG data. The recent introduction of chronotaxic systems provides a theoretical framework within which dynamical systems can have amplitudes and frequencies which are time-varying, yet remain stable, matching well the characteristics of life. We demonstrate that, when applied in the context of chronotaxic systems, the methods presented facilitate the accurate extraction of the system dynamics over many scales of time and space.
关键词： phase coherence,coupling function,Biomedical signal analysis,dynamical Bayesian inference,wavelet bispectrum,cardiovascular system,time-frequency analysis,brain dynamics,time-dependent dynamics
更新于2025-09-19 17:13:59
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Acoustic emission-based characterization of focal position during ultra-short pulse laser ablation
摘要： Microstructures were ablated using an ultra-short pulse laser system in order to investigate the influence of focal position on the surface topography. In addition, acoustic emissions measured by a piezoelectric sensor adapted to the AISI 4140 workpiece were analyzed and correlated with the focal position and the resulting surface topography. Frequency ranges sensitive to variations of the z-axis position were determined by STFT analysis. Subsequently, significant signal components were processed to enable an inference about the focal position. The hypothesis of assessing the focal position in-process based on acoustic emissions to ensure high precision during laser ablation could be confirmed.
关键词： modulation,time-frequency analysis,acoustic emission,laser ablation,focal position
更新于2025-09-12 10:27:22
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Effective Defect Features Extraction for Laser Ultrasonic Signal Processing by Using Time–Frequency Analysis
摘要： The time-frequency analysis (TFA) by wavelet transform is adopted for the laser ultrasonic signal processing, and the effective features extraction of the material defect is obtained. The TFA is adopted here to analyze the laser-generated surface acoustic wave (SAW) signal which contains the defect features, the echo wave features are extracted signi?cantly, especially under the condition of low signal-to-noise rate (SNR). The simulation model by using ?nite element method (FEM) is set up in an aluminum plate with different surface defect depths in detail, and the defect depths prediction with TFA is also considered. It shows that, without extra denoising process, the echo SAW is extracted signi?cantly in case of defect depths ranging from 0.1mm to 0.9mm at SNR of ?3dB by TFA. The TFA for processing the laser ultrasonic signal provides a promising way to get the defect information, with the accuracy increased by 7.9dB in this work, which is extremely meaningful for the ultrasonic signal processing and material evaluation.
关键词： Time-frequency analysis,feature extraction,wavelet transform,signal-to-noise rate,laser ultrasonic signal
更新于2025-09-11 14:15:04
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Extraction of micro-doppler characteristics of drones using high-resolution time-frequency transforms
摘要： The demand for detecting and tracking drones has increased for reasons of surveillance and security. Radar is one of the promising methods in this regard. The recognition and identification of drones using a radar system requires the extraction of their unique micro-Doppler signatures produced by their rotating blades. Because of the blades’ rapid rotation speed, difficulties are inherent in visualizing clear micro-Doppler signatures in a conventional joint time-frequency analysis such as the short-time Fourier transform. In this paper, we propose the use of high-resolution transform techniques to visualize the micro-Doppler signatures of drones in a spectrogram. The techniques used include Wigner-Ville distribution, smoothed pseudo-Wigner-Ville distribution, and short-time MUltiple SIgnal Classification (MUSIC) algorithm. In particular, the latter, which had never previously been applied to drones, is suggested to visualize the details of micro-Doppler signatures. We measured three drones using a continuous-wave radar, and performances of these algorithms were compared using data collected from the drones. We could observe that the short-time MUSIC method showed the clearest spectrogram for identifying micro-Doppler signatures. This study can potentially be useful in the field of drone classification.
关键词： micro-Doppler Signatures,Wigner Ville distribution,Time-frequency MUSIC,Joint time-frequency Analysis
更新于2025-09-09 09:28:46