The growing demand for bandwidth makes photonic systems a leading candidate for future telecommunication and radar technologies. Integrated photonic systems offer ultra-wideband performance within a small footprint, which can naturally interface with fiber-optic networks for signal transmission. However, it remains challenging to realize narrowband (∼MHz) filters needed for high-performance communications systems using integrated photonics. In this paper, we demonstrate all-silicon microwave-photonic notch filters with 50× higher spectral resolution than previously realized in silicon photonics. This enhanced performance is achieved by utilizing optomechanical interactions to access long-lived phonons, greatly extending available coherence times in silicon. We use a multi-port Brillouin-based optomechanical system to demonstrate ultra-narrowband (2.7 MHz) notch filters with high rejection (57 dB) and frequency tunability over a wide spectral band (6 GHz) within a microwave-photonic link. We accomplish this with an all-silicon waveguide system, using CMOS-compatible fabrication techniques.
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http://dx.doi.org/10.1038/s41467-022-29590-0 | DOI Listing |
Sensors (Basel)
November 2024
Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China.
Railway traction motor bearings (RTMB) are critical components in high-speed trains (HST) that are particularly susceptible to failure due to the high stress and rotational frequency they experience. To address the challenge of high false-positive rates in existing monitoring systems, this paper introduces a novel sensorless monitoring scheme that leverages stator current to detect fault-related characteristics, eliminating the need for additional sensors. This approach employs a hybrid signal preprocessing algorithm that integrates adaptive notch filtering (ANF) with envelope spectrum analysis (ESA) to effectively sparse the stator current and extract relevant fault features.
View Article and Find Full Text PDFMolecules
November 2024
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Miniaturized spectrometers have significantly advanced real-time analytical capabilities in fields such as environmental monitoring, healthcare diagnostics, and industrial quality control by enabling precise on-site spectral analysis. However, achieving high sensitivity and spectral resolution within compact devices remains a significant challenge, particularly when detecting low-concentration analytes or subtle spectral variations critical for chemical and molecular analysis. This study introduces an innovative approach employing guided-mode resonance filters (GMRFs) to address these limitations.
View Article and Find Full Text PDFMuscle Nerve
December 2024
Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Electrical Interference (EI: radiated electromagnetic and/or power line interference) is a common problem in clinical neurophysiology with many causes and thus various conceivable solutions. Although newer digitized electrodiagnostic (EDX) systems have markedly reduced EI issues, it remains a possible impediment in achieving high quality studies. So that the electrodiagnostic medicine consultant (EMC) can problem solve EI, this monograph details the fundamental functional concepts and terminology of electronic amplification and recording electrodes from a practical perspective.
View Article and Find Full Text PDFISA Trans
December 2024
Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China. Electronic address:
To identify the frequency and amplitude of a periodic signal in real-time, a novel approach termed the "Online Harmonics Extraction Approach (OHEA)" is proposed in this paper. This method employs a notch filter with an adjustable center frequency to identify the frequency of periodic signals accurately. The computation of the envelope curve and phase-sensitive detection are combined to identify the signal amplitude and smooth out transient stages.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Key Laboratory of Deep Petroleum Intelligent Exploration and Development, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China.
Seismic data acquired in the presence of mechanical vibrations or power facilities may be contaminated by strong interferences, significantly decreasing the data signal-to-noise ratio (S/N). Conventional methods, such as the notch filter and time-frequency transform method, are usually inadequate for suppressing non-stationary interference noises, and may distort effective signals if overprocessing. In this study, we propose a method for eliminating mechanical vibration interferences in seismic data.
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