A 1.5D Spectral Kurtosis-Guided TQWT Method and Its Application in Bearing Fault Detection

Bearings are the key parts of rotating machinery, and their operation status is related to the operation safety of the whole equipment. Vibration signals often contain periodic impulse components which can reflect the fault state of bearings. However, due to the interference of signal transmission path and the influence of operating environment noise, the periodic impulse components in the signal are often submerged by the nonperiodic transient impulse components, modulation harmonic components, and noise components. Therefore, the core problem of bearing fault diagnosis theory is used to accurately extract the frequency band of bearing fault state information and suppress the frequency band of interference information. In this paper, the signal is processed by the tunable Q-factor wavelet transform (TQWT), the midfrequency band of the signal is tightly divided by selecting different Q-values, and the 1.5D spectral kurtosis defined in frequency domain is used to select the optimal subband. Simulated analysis shows that this method can avoid low-frequency harmonic interference, nonperiodic transient impulse components, and strong noise components in the time domain. Therefore, it can effectively realize the selection of the subbands of periodic impulse components and effectively extract fault feature information. Through experimental signal analysis, TQWT has good sparsity decomposition characteristics and can reasonably divide the signal frequency band, so as to separate the useful fault characteristic frequency band and interference frequency band. At the same time, compared with the kurtosis index, 1.5D spectral kurtosis has better robustness and resolution for low signal-to-noise ratio signals, which can achieve the purpose of fault characteristic band extraction.

Download Full-text

Compound Fault Diagnosis of Bearings Using an Improved Spectral Kurtosis by MCDK

Mathematical Problems in Engineering ◽

10.1155/2018/6513045 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12 ◽

Cited By ~ 8

Author(s):

Shuting Wan ◽

Xiong Zhang ◽

Longjiang Dou

Keyword(s):

Resonant Frequency ◽

Frequency Band ◽

Practical Applications ◽

Noise Interference ◽

Spectral Kurtosis ◽

Modified Method ◽

Weak Fault ◽

Fault Information ◽

Demodulation Method ◽

Fault Characteristic

The fast spectrum kurtosis (FSK) algorithm can adaptively identify and select the resonant frequency band and extract the fault feature by the envelope demodulation method. However, in practical applications, the fault source may be located in different resonant frequency bands; plus in noise interference, the weak side of the compound fault is not easy to be identified by the FSK. In order to improve the accuracy of fast spectral kurtosis analysis method, a modified method based on maximum correlation kurtosis deconvolution (MCKD) is proposed. According to the possible fault characteristic frequencies, the period of MCKD is calculated, and the appropriate filter length is selected to filter the original compound fault signal. In this way, the compound fault located in different resonance bands is separated. Then, the signal after MCKD filtering is analyzed by FSK. Through the simulation and experimental analysis, the MCKD can separate the compound fault information in different frequency band and eliminate the noise interference; the FSK can accurately identify the resonance frequency and identify the weak fault characteristics of compound fault.

Download Full-text

Influence of the radio signals frequency band on their spatial selection in communication channels

E3S Web of Conferences ◽

10.1051/e3sconf/202127902002 ◽

2021 ◽

Vol 279 ◽

pp. 02002

Author(s):

Alexander Okorochkov ◽

Nadezda Dmitrienko

Keyword(s):

Frequency Band ◽

Signal To Noise Ratio ◽

Radio Channel ◽

Signal Transmission ◽

Total Field ◽

Sharp Drop ◽

Single Carrier ◽

Channel Bandwidth ◽

Radio Signals ◽

Reception Area

This article deals with the dependence of the signal-to-noise ratio (S/N) on the frequency band of a radio channel when transmitting three different radio signals over it based on a mathematical model. Signals are transmitted on a single carrier frequency, in one direction and occupy the entire channel frequency band, which varied from 0 to 30 GHz. A threeelement sparse antenna array (SAA) is used for signal transmission. Each signal is emitted by all three SAA elements with certain phase shifts. In the reception area, such a structure of the total field is formed, at which the maxima of all transmitted signals are spatially spaced. This allows each signal to be received on a separate antenna. Studies have shown that the S/N ratio for different signals depends differently on the channel bandwidth. For a signal emitted by all SAA antennas in phase, the S/N ratio is practically independent of the bandwidth and is about 70 dB. For the two remaining phased signals the S/N ratio varies equally over the entire range of the channel frequency band values and is characterized by a sharp drop from 62 to 8 dB.

Download Full-text

Ultrasonic frogs call at a higher pitch in noisier ambiance

Current Zoology ◽

10.1093/czoolo/61.6.996 ◽

2015 ◽

Vol 61 (6) ◽

pp. 996-1003 ◽

Cited By ~ 10

Author(s):

Fang Zhang ◽

Pan Chen ◽

Zhuqing Chen ◽

Juan Zhao

Keyword(s):

Fundamental Frequency ◽

Signal To Noise Ratio ◽

Low Frequency ◽

Environmental Noise ◽

Central China ◽

Signal Frequency ◽

Frequency Noise ◽

Acoustic Adaptation ◽

Adaptation Hypothesis ◽

Acoustic Adaptation Hypothesis

Abstract The ultrasonic communication in Concave-eared torrent frogs Odorrana tormota is believed to be an adaptation to avoid masking by the intense low-frequency noise of the rushing stream in their habitat. The acoustic adaptation hypothesis for ultrasonic origin predicts that some organisms subjecting to persistent acoustic interference from broadband, low-frequency environmental noise, might shift their signal frequency upward into frequency bands with lower noise energy. In other words, low-frequency environmental noise might cause upward shifts of species’ vocalization frequencies making their signals more conspicuous. Presently, it is unclear whether male O. tormota adjust their signal features in response to a change in the ambient noise level. We tested the prediction of the acoustic adaptation hypothesis by recording the vocalizations of male O. tormota inhabiting two streams with different background noise levels in Huangshan in central China and comparing their call features including the fundamental frequency (F0). Results showed that the spectrotemporal characteristics of the vocal signals of males in the two habitats were indifferent, except the duration of the call harmonic segments and three parameters related to the call fundamental frequency (F0). In terms of the F0, the pooled and individual frog data showed that frogs inhabiting the noisier habitat tended to emit calls having higher F0. The higher F0 increases the signal-to-noise ratio, thus benefiting the detection of vocalization. Thus, similar to several anuran species, concave-eared torrent frogs also display noise-dependent adjustment of vocal pitch in their vocalizations for making them more audible.

Download Full-text

Variations in broadband seismic noise at IRIS/IDA stations in the USSR with implications for event detection

Bulletin of the Seismological Society of America ◽

10.1785/bssa08006b2072 ◽

1990 ◽

Vol 80 (6B) ◽

pp. 2072-2088 ◽

Cited By ~ 7

Author(s):

Holly K. Given

Keyword(s):

Noise Reduction ◽

High Frequency ◽

Signal To Noise Ratio ◽

Low Frequency ◽

Time Of Day ◽

Signal Frequency ◽

Seasonal Effect ◽

Noise Levels ◽

Power Spectral ◽

Lower Noise

Abstract Ambient noise conditions at four IRIS/IDA sites in the USSR are characterized from 0.01 to 100 Hz as part of a study to ascertain the utility of broadband three-component seismic stations in monitoring regional Eurasian seismicity. Estimates of the power spectral density of noise levels were computed for a 5-day period in two seasons (winter and summer), at two times of the day. Of these periods, lower noise conditions were found at night in the summer. In general, at 1 Hz and above, noise levels and their variations correlate predictably with the soundness of vault construction and the proximity of the station to civilization. Absolute noise levels at the IRIS/IDA/USSR sites range from a high of about −120 dB to a low of −155 dB relative to (1 m/s2)2/Hz, between 1 and 5 Hz. A time-of-day variation in noise was observed at all sites, with noise levels during the work day ranging from 7 to 14 dB higher than night levels, depending on the site. This effect was observed only for frequencies above about 1 Hz. Observed seasonal variations (winter versus summer) are highly station dependent, although the seasonal effect is restricted to frequencies below 1 Hz and is in general centered on the microseism peak (0.1 to 0.2 Hz). Below 0.1 Hz, noise levels are influenced by the thermal and barometric isolation of the site. Low-frequency levels were not studied below 0.01 Hz. Minimum detectable magnitudes are estimated for the IRIS/IDA stations using the observed noise levels over 1 Hz. In general, a magnitude 3 event should be detectable at 1,000 km by all stations under night noise conditions if the dominant signal frequency is 1 Hz; the magnitude estimates increase with increasing frequency. These detectability estimates assume a conservative signal-to-noise ratio of 6. High-frequency data recorded by independent equipment co-located with the IRIS/IDA system during a 2-week experiment allow estimation of noise levels at the sites up to 100 Hz. Borehole versus surface noise levels recorded during the high-frequency experiment showed significant noise reduction (20 dB) can be achieved by borehole deployment at sites with exposed surface vaults. With well-isolated surface vaults, borehole noise reduction is about a factor of 2. Absolute noise levels between 1 to 10 Hz observed at IRIS/IDA/USSR sites are systematically higher than average NORESS noise by about 7 dB to 25 dB, depending on the station.

Download Full-text

Rolling Bearing Fault Feature Extraction Based on Adaptive Tunable Q-Factor Wavelet Transform and Spectral Kurtosis

Shock and Vibration ◽

10.1155/2020/8875179 ◽

2020 ◽

Vol 2020 ◽

pp. 1-19

Author(s):

Jianlong Zhao ◽

Yongchao Zhang ◽

Qingguang Chen

Keyword(s):

Feature Extraction ◽

Wavelet Transform ◽

Frequency Band ◽

Rolling Bearing ◽

Band Pass Filter ◽

Q Factor ◽

Bearing Fault ◽

Spectral Kurtosis ◽

Manual Selection ◽

Weak Fault

The fault feature of the rolling bearing is difficult to extract when weak fault occurs and interference exists. The tunable Q-factor wavelet transform (TQWT) can effectively extract the weak fault characteristic of the rolling bearing, but the manual selection of the Q-factor affects the decomposition result and only using TQWT presents interference. Aiming at the above problems, an adaptive tunable Q-factor wavelet transform (ATQWT) and spectral kurtosis (SK) method is proposed in this paper. Firstly, the method applies particle swarm optimization (PSO) to seek the optimized Q-factor for avoiding manual selection, which uses the kurtosis value of the transient impact component as the particle fitness function. The rolling bearing fault signal is decomposed into continuous oscillation component and transient impact component containing fault feature by the optimized Q-factor. Then, due to the presence of interference in the decomposition result of ATQWT, the SK analysis of the transient impact component is used to determine the frequency band of periodic impact component characterizing fault feature by fast kurtogram. Finally, the band-pass filter established through the above frequency band is employed to filter the interference in the transient impact component. Simulation and experimental results indicate that the ATQWT can highlight the periodic impact component characterizing rolling bearing fault feature, and the SK can filter interference in the transient impact component, which improves feature extraction effect and has great significance to enhance fault diagnosis accuracy of the rolling bearing. Compared with EEMD-TQWT and TQWT-SK, the fault feature extracted by the proposed method is prominent and effective.

Download Full-text

Noise-Induced Tuning Curve Changes in Mechanoreceptors

Journal of Neurophysiology ◽

10.1152/jn.1998.79.4.1879 ◽

1998 ◽

Vol 79 (4) ◽

pp. 1879-1890 ◽

Cited By ~ 33

Author(s):

Chandra Ivey ◽

A. Vania Apkarian ◽

Dante R. Chialvo

Keyword(s):

Tuning Curve ◽

Signal To Noise Ratio ◽

Signal Transmission ◽

Low Frequency ◽

External Noise ◽

Sine Wave ◽

Tuning Curves ◽

Large Expansion ◽

Typical Shape ◽

Noise Input

Ivey, Chandra, A. Vania Apkarian, and Dante R. Chialvo. Noise-induced tuning curve changes in mechanoreceptors. J. Neurophysiol. 79: 1879–1890, 1998. Fibers from the tibial nerve of rat were isolated and spike activity recorded using monopolar hook electrodes. The receptive field (RF) of each recorded unit on the glabrous skin of the foot was mechanically stimulated with waveforms comprised of various frequency sine waves in addition to increasing levels of white noise. Single-unit responses were recorded for both rapidly adapting (RA) and slowly adapting (SA) units. Signal-to-noise ratio (SNR) of the output was quantified by the correlation coefficient ( C 1) between the input sine wave and the nerve responses. The addition of noise enhanced signal transmission in both RA and SA fibers. With increasing noise, the initially inverted “V”-shaped, zero-noise tuning curves for RA fibers broadened and eventually inverted. There was a large expansion of the frequencies that the RA receptor responded to with increasing noise input. On the other hand, the typical shape of the SA fiber tuning curves remained invariant, at all noise levels tested. C 1 values continued to increase with larger noise input for higher frequencies, but did not do so at the lowest frequencies. For both RA and SA fibers the responses with added noise tended to be rate modulated at the low-frequency end, and followed nonlinear stochastic resonance (SR) properties at the higher frequencies. The changes in the tuning properties due to noise found here, as well as preliminary psychophysics data, imply that external noise is relevant for sensing small periodic signals in the environment. All current models of sensory perception assume that the tuning properties of receptors determined in the absence of noise are preserved during everyday tasks. Our results indicate that this is not true in a noisy environment.

Download Full-text

Application of Time Synchronous Averaging, Spectral Kurtosis and Support Vector Machines for Bearing Fault Identification

Volume 7: Operations, Applications and Components ◽

10.1115/pvp2008-61601 ◽

2008 ◽

Cited By ~ 1

Author(s):

Christian N. Komgom ◽

Njuki W. Mureithi ◽

Aouni A. Lakis

Keyword(s):

Signal Processing ◽

Support Vector Machines ◽

Signal Transmission ◽

Spectral Energy ◽

Support Vector ◽

Generalization Performance ◽

Transmission Path ◽

Bearing Fault ◽

Spectral Kurtosis ◽

Vector Machines

Condition monitoring of rolling elements bearings is investigated in this paper. Recently [12, 13], we have developed a diagnosis procedure that combines a signal processing tool, i.e. Time Synchronous Averaging (TSA), and a pattern recognition method, i.e. Support Vector Machines (SVM), for bearing fault detection and prediction. As the generalization performance of the SVM-boundaries was strongly affected by the signal transmission path, this paper is then concerned with the integration of Spectral Kurtosis (SK) analysis in the diagnosis procedure to improve efficiency in such cases. We validate the use of both Time Synchronous Averaging and Spectral Kurtosis analysis, as signal processing tools that will automatically highlight bearing defect frequencies in the envelope spectrum. Twenty-one features (rms, peak, crest factor, band spectral energy, etc...) are extracted from the envelope of signals obtained from these two analyses and are used in the learning scheme. Results show that the generalization performance is less affected by the signal transmission path and the faulty bearing location, thus demonstrating that the modified diagnosis procedure can actually find some underlying patterns that are common to each type of bearing failure. The case-dependency of the support decision tool can therefore be reduced.

Download Full-text

Scope Out Multiband Gravitational-Wave Observations of GW190521-Like Binary Black Holes with Space Gravitational Wave Antenna B-DECIGO

Universe ◽

10.3390/universe7030053 ◽

2021 ◽

Vol 7 (3) ◽

pp. 53

Author(s):

Hiroyuki Nakano ◽

Ryuichi Fujita ◽

Soichiro Isoyama ◽

Norichika Sago

Keyword(s):

Black Holes ◽

Gravitational Wave ◽

Frequency Band ◽

Strong Field ◽

Signal To Noise Ratio ◽

Low Frequency ◽

Next Generation ◽

Estimation Errors ◽

Tests Of General Relativity ◽

Wave Signal

The gravitational wave event, GW190521, is the most massive binary black hole merger observed by ground-based gravitational wave observatories LIGO/Virgo to date. While the observed gravitational wave signal is mainly in the merger and ringdown phases, the inspiral gravitational wave signal of the GW190521-like binary will be more visible to space-based detectors in the low-frequency band. In addition, the ringdown gravitational wave signal will be louder in the next generation (3G) of ground-based detectors in the high-frequency band, displaying the great potential of multiband gravitational wave observations. In this paper, we explore the scientific potential of multiband observations of GW190521-like binaries with a milli-Hz gravitational wave observatory: LISA; a deci-Hz observatory: B-DECIGO; and (next generation of) hecto-Hz observatories: aLIGO and ET. In the case of quasicircular evolution, the triple-band observations of LISA, B-DECIGO, and ET will provide parameter estimation errors of the masses and spin amplitudes of component black holes at the level of order of 1–10%. This would allow consistency tests of general relativity in the strong field at an unparalleled precision, particularly with the “B-DECIGO + ET” observation. In the case of eccentric evolution, the multiband signal-to-noise ratio found in “B-DECIGO + ET” observation would be larger than 100 for a five-year observation prior to coalescence, even with high final eccentricities.

Download Full-text