Fault diagnosis of rolling bearings based on improved direct fast iterative filtering and spectral amplitude modulation

As the transient impulse components in early fault signals are weak and easily buried by strong background noise, the fault features of rolling bearings are difficult to be extracted effectively. Focusing on this issue, a novel method based on improved direct fast iterative filtering and spectral amplitude modulation (IDFIF-SAM) is presented for detecting the early fault of rolling bearings. First, the ratio of the average crest factor of autocorrelation envelope spectrum to the average envelope entropy is taken as the fitness function to search the optimal parameters of direct fast iterative filtering (DFIF) adaptively via particle swarm optimization (PSO). Then, the efficient kurtosis entropy (EKE) index is being employed to choose the suitable components to reconstruct the signal. Finally, the reconstructed signal is subjected to spectral amplitude modulation (SAM) to strengthen the impulse features. The superiority of improved direct fast iterative filtering (IDFIF) over fixed-parameter DFIF, fast iterative filtering (FIF), and hard thresholding fast iterative filtering (HTFIF) is clarified through the simulated signal. Moreover, the comparative experimental analysis shows that the proposed IDFIF-SAM method can identify the early fault feature of rolling bearings more effectively.

A New Speech Enhancement Technique Based on Stationary Bionic Wavelet Transform and MMSE Estimate of Spectral Amplitude

Speech enhancement has gained considerable attention in the employment of speech transmission via the communication channel, speaker identification, speech-based biometric systems, video conference, hearing aids, mobile phones, voice conversion, microphones, and so on. The background noise processing is needed for designing a successful speech enhancement system. In this work, a new speech enhancement technique based on Stationary Bionic Wavelet Transform (SBWT) and Minimum Mean Square Error (MMSE) Estimate of Spectral Amplitude is proposed. This technique consists at the first step in applying the SBWT to the noisy speech signal, in order to obtain eight noisy wavelet coefficients. The denoising of each of those coefficients is performed through the application of the denoising method based on MMSE Estimate of Spectral Amplitude. The SBWT inverse, S B W T − 1 , is applied to the obtained denoised stationary wavelet coefficients for finally obtaining the enhanced speech signal. The proposed technique’s performance is proved by the calculation of the Signal to Noise Ratio (SNR), the Segmental SNR (SSNR), and the Perceptual Evaluation of Speech Quality (PESQ).

Full characterization of a phase-locked DUV double pulse generated in an all-reflective shaping setup working under grazing incidence in a broad spectral range

Controlling the temporal and spectral properties of ultrashort laser pulses in the visible and near-infrared spectral range by means of a femtosecond pulse-shaping device is a powerful tool with many applications in ultrafast spectroscopy. A major and successful concept is known as the 4f design, which has a symmetric zero-dispersion-compressor geometry. Most 4f pulse shapers rely on using transmissive optics in their beam path limiting the operational wavelength ranges. In the present contribution, we use an all-reflective shaping setup to generate a phase-locked 266 nm double pulse to benchmark its performance in the limit of short wavelengths. The setup comprises the complete spectral amplitude and phase diagnostics for quantitative analysis of the pulse properties before and after the shaper using the technique of frequency-resolved optical gating. The measured time–frequency spectra are in good agreement with optical simulations. The geometry and hardware of the device including the optical components are designed, such that all harmonics of the deep UV pulses travel the same path, giving the instrument the ability to work with soft X-ray pulses, under vacuum conditions, down to the few-nanometer wavelength scale.

Specific Posture-Stabilising Effects of Vision and Touch Are Revealed by Distinct Changes of Body Oscillation Frequencies

We addressed postural instability during stance with eyes closed (EC) on a compliant surface in healthy young people. Spectral analysis of the centre of foot pressure oscillations was used to identify the effects of haptic information (light-touch, EC-LT), or vision (eyes open, EO), or both (EO-LT). Spectral median frequency was strongly reduced by EO and EO-LT, while spectral amplitude was reduced by all “stabilising” sensory conditions. Reduction in spectrum level by EO mainly appeared in the high-frequency range. Reduction by LT was much larger than that induced by the vision in the low-frequency range, less so in the high-frequency range. Touch and vision together produced a fall in spectral amplitude across all windows, more so in anteroposterior (AP) direction. Lowermost frequencies contributed poorly to geometric measures (sway path and area) for all sensory conditions. The same subjects participated in control experiments on a solid base of support. Median frequency and amplitude of the spectrum and geometric measures were largely smaller when standing on solid than on foam base but poorly affected by the sensory conditions. Frequency analysis but not geometric measures allowed to disclose unique tuning of the postural control mode by haptic and visual information. During standing on foam, the vision did not reduce low-frequency oscillations, while touch diminished the entire spectrum, except for the medium-high frequencies, as if sway reduction by touch would rely on rapid balance corrections. The combination of frequency analysis with sensory conditions is a promising approach to explore altered postural mechanisms and prospective interventions in subjects with central or peripheral nervous system disorders.

Modulation of gamma spectral amplitude and connectivity during reaching predicts peak velocity and movement duration

Voluntary movements are accompanied by increased oscillatory activity or synchronization in the gamma range (> 25.5 Hz) within the sensorimotor system. Despite the extensive literature about movement-related gamma synchronization, the specific role of gamma oscillations for movement control is still debated. In this study, we characterized movement-related gamma oscillatory dynamics and its relationship with movement characteristics based on 256-channels EEG recordings in 64 healthy subjects while performing fast and uncorrected reaching movements to targets located at three distances. We found that movement-related gamma synchronization occurred during both movement planning and execution, albeit with different gamma peak frequencies and topographies. Also, the amplitude of gamma synchronization in both planning and execution increased with target distance. Additional analysis of phase coherence revealed a gamma-coordinated long-range network involving occipital, frontal and central regions during movement execution. Gamma synchronization amplitude and phase coherence pattern reliably predicted peak velocity amplitude and timing, thus suggesting that cortical gamma oscillations play a significant role in the selection of appropriate kinematic parameters during planning and in their implementation during movement execution.

Modeling Seismic Network Detection Thresholds Using Production Picking Algorithms

Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data-driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well-sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

Wiener Gain and Deep Neural Networks: A Well-Balanced Pair For Speech Enhancement

This paper proposes a Deep Neural Network (DNN)-based Wiener gain estimator for speech enhancement. The proposal is in the framework of the classical spectral-domain speech enhancement algorithms. In this case, we used the Optimal Modified Log-Spectral Amplitude (OMLSA), but consider that this proposal could fit many alternative speech estimation algorithms. We determined the best usage of the DNN approach at learning a robust instance of the Wiener gain estimator according to the characteristics of the SNR estimation and the gain function. To design a DNN architecture adjusted for the speech enhancement task, we study various configuration issues frequently used in DNN-based solutions, including speech representations, residual connections, and causal vs. non-causal designs. Thus, we provide conclusions for the use of DNN architectures with the enhancement purpose. Experiments show that the proposal provides results on the state-of-the-art. But beyond the objective quality measures, there are examples of noisy vs. enhanced speech available for listening to demonstrate in practice the skills of the method in real audio.