REFLECTED AND TRANSMITTED FILTER FUNCTIONS FOR SIMPLE SUBSURFACE GEOMETRIES

Geophysics ◽  
1976 ◽  
Vol 41 (6) ◽  
pp. 1305-1317 ◽  
Author(s):  
M. Schoenberger ◽  
F. K. Levin
Keyword(s):  
Thin Layer ◽  
High Frequency ◽  
Narrow Band ◽  
Broad Band ◽  
Low Frequency ◽  
Single Layer ◽  
High Amplitude ◽  
Shadow Zone ◽  
Least Energy ◽  
Very High

A zone of sands embedded in shale acts as a filter, both in reflecting energy back to the surface and in transmitting energy to reflectors below them. For a single layer of sand, the reflection filter is periodic—reflecting no energy at some frequencies and more than either of the two individual interfaces at other frequencies. Separating the sand zone into two parts by inserting a thin layer of shale results in reflection filters which differ greatly from one another. The particular filter curve generated depends upon the location of the shale layer. A sand zone filters reflections from interfaces below the zone in a manner complementary to the reflection filter. Where the most energy is reflected, the least is transmitted; conversely, where the least energy is reflected, the most is transmitted. The models considered in this report could easily give rise to high‐amplitude reflections; but, unless the amplitudes were very high, there would be little filtering of deeper reflections. However, for very high‐amplitude reflections and narrow‐band data, little energy would be transmitted and a shadow zone would result. For very high‐amplitude shallow reflections and broad‐band data, a low‐frequency shallow reflection would cause high‐frequency deep reflections; a high‐frequency shallow reflection would cause low‐frequency deep reflections.

Disparity Modulation Sensitivity for Narrow-Band-Filtered Stereograms Viewed out of the Plane of Fixation

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 94-94
Author(s):  
B Lee ◽  
B J Rogers
Keyword(s):  
Spatial Frequency ◽  
High Frequency ◽  
Significant Interaction ◽  
Narrow Band ◽  
Low Frequency ◽  
Frequency Pattern ◽  
Spatial Frequencies ◽  
Size Disparity ◽  
Random Dot Stereograms

Narrow-band-filtered random-dot stereograms were used to determine stereo thresholds for detecting sinusoidal disparity modulations. These stereograms were designed to stimulate selectively channels tuned to luminance and corrugation spatial frequencies (Schumer and Ganz, 1979 Vision Research19 1303 – 1314). Thresholds were determined for corrugation frequencies ranging from 0.125 to 1 cycle deg−1, luminance centre spatial frequencies ranging from 1 to 8 cycles deg−1 and disparity pedestal sizes ranging from −32 to +32 min arc. For small disparity pedestals, lowest modulation thresholds were found around 0.5 cycle deg−1 corrugation frequency and 4 cycles deg−1 luminance centre spatial frequency. For large disparity pedestals (±32 arc min), lowest thresholds were shifted towards the lower corrugation frequencies (0.125 cycle deg−1) and lower luminance frequencies (2 cycles deg−1). There was a significant interaction between luminance spatial frequency and disparity pedestal size. For small pedestals, lowest thresholds were found with the highest luminance frequency pattern (4 cycles deg−1). For large pedestals, best performance shifted towards the low-frequency patterns (1 cycle deg−1). This effect demonstrates a massive reduction in stereo-efficiency for high-frequency patterns in the luminance domain at large disparity pedestals which is consistent with the ‘size-disparity relation’ proposed by previous researchers.

Reduction of Vibration and Noise Generated by Planetary Ring Gears in Helicopter Aircraft Transmissions

1973 ◽  
Vol 95 (4) ◽  
pp. 1149-1158 ◽  
Author(s):  
Thomas Chiang ◽  
R. H. Badgley
Keyword(s):  
High Frequency ◽  
Narrow Band ◽  
Vibration Energy ◽  
Ring Gear ◽  
Noise Sources ◽  
Rotor Drive ◽  
Design Changes ◽  
Planetary Ring ◽  
Gear Meshes ◽  
Very High

Rotor-drive gearboxes are major noise sources in helicopter aircraft. Narrow-band examination of this noise often indicates the presence of several or more very high, narrow noise peaks, which are located at gearbox mesh frequencies or their multiples. Important exceptions are sideband noise components, located so near the main signal component as to be indistinguishable except by very narrow band reduction. Noise of this type is most effectively treated through a systematic study of the flow of high-frequency vibration energy in the drive train. Such studies should examine the mechanism by which gear meshes generate vibrations, and the vibration response of the gearbox components which support the gears. Results of such calculations are presented for the planetary reduction ring-gear casing elements in the Boeing-Vertol CH-47 forward rotor-drive gearbox and the Bell UH-1D main rotor-drive gearbox. The calculations indicate logical reasons why noise is generated. Typical ring-gear casing design changes are examined for noise reduction.

The Motion of Strawberry Leaves in an Air-Assisted Spray Field and its Influence on Droplet Deposition

2021 ◽  
Vol 64 (1) ◽  
pp. 83-93
Author(s):  
Shuo Wu ◽  
Jizhan Liu ◽  
Jiangshan Wang ◽  
Dianhe Hao ◽  
Rongkai Wang
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
High Amplitude ◽  
Azimuth Angle ◽  
List Type ◽  
Droplet Deposition ◽  
Inclination Angles ◽  
Turbulence Effect ◽  
Spray Field ◽  
Low Amplitude

HighlightsA visualization method for the motion of strawberry leaves in an air-assisted spray field is proposed.Strawberry leaves showed two motion states in different critical velocity ranges of the sprayer airflow.The airflow instability and the turbulence effect are considered important factors for the leaf vibrations.A strawberry leaf azimuth angle in the range of 90° to 270° can provide good deposition with smaller droplets.Abstract. The reasonable motion of crop plants in an air-assisted spray field can improve droplet deposition. Therefore, this study focuses on the motion of strawberry leaves and the droplet deposition mechanism in an air-assisted spray field. First, this study proposes a descriptive method for strawberry leaf motion in an air-assisted spray field and clarifies the important influence of strawberry leaf motion on droplet deposition. Second, an experiment was performed on the motion and droplet capture of single strawberry leaves in multi-position postures in an air-assisted spray field. The results showed that the leaves had two motion states (i.e., low amplitude with low frequency and high amplitude with high frequency) at different airflow velocities and inclination angles, and the critical airflow velocity corresponding to the two motion states was determined to be 8.7 m s-1. When the azimuth angle of the strawberry leaves is in the range of 90° to 270°, a reasonable inclination angle of the airflow and the high frequency and high amplitude vibration state of the leaves driven by the airflow will provide good deposition and canopy penetration of droplets with smaller diameters. Keywords: Air-assisted spray field, Droplet deposition, Motion, Spray, Strawberry leaves.

High-Level Psychophysical Tuning Curves

1991 ◽  
Vol 34 (2) ◽  
pp. 360-373 ◽  
Author(s):  
David A. Nelson ◽  
Todd W. Fortune
Keyword(s):  
Background Noise ◽  
Pure Tone ◽  
Narrow Band ◽  
Tuning Curve ◽  
Broad Band ◽  
Low Frequency ◽  
Tuning Curves ◽  
Tuning Characteristic ◽  
High Level ◽  
Combination Bands

Simultaneous-masked psychophysical tuning curves were obtained from normal-hearing listeners using low-level (20–25 dB SPL) probe tones in quiet and high-level (60 dB SPL) probe tones, both in quiet and in the presence of a broad-band background noise. The background noise was introduced to eliminate combination tones or combination bands and other off-frequency listening cues that exist at high levels. Tuning curves were obtained using pure-tone maskers and 100-Hz-wide narrow-band noise maskers for probe tones at 1000 and 4000 Hz. High-level tuning curves for pure-tone maskers demonstrated large discontinuities or “notches” on the low-frequency sides of the tuning curves. Broad-band background noise eliminated those notches, indicating that the notches were due to the detection of off-frequency listening cues at combination-tone frequencies. High-level tuning curves for 100-Hz-wide narrow-band maskers also demonstrated notches on the low-frequency sides. Those notches were eliminated with broad-band background noise, which indicates that combination bands strongly influenced the shapes of high-level tuning curves obtained with narrow-band maskers. The influence of combination bands was dependent upon test frequency. At 1000 Hz, combination bands had very little influence on the shapes of high-level tuning curves. At 4000 Hz, where the masker bandwidth was substantially less than the critical bandwidth, combination bands strongly affected the low-frequency sides of the tuning curves. In 2 subjects tested at a probe frequency of 2000 Hz with 100-Hz-wide masking bands, combination bands also influenced the lowfrequency sides of high-level tuning curves. The presence of combination-tone or combination-band cues essentially steepened the low-frequency slopes of tuning curves, resulting in sharper estimates of tuning. Comparisons of tuning curves obtained with pure-tone maskers and narrow-band maskers, in the same listeners, revealed that pure-tone maskers were more effective than narrow-band maskers when the masker frequencies were in the tail region of the tuning curve. The results of these experiments support the notion that tuning in the normal auditory system broadens notably with stimulus level, once off-frequency listening cues such as combination tones or combination bands are eliminated. The low-level simultaneously masked tuning curve demonstrates a sharp bandpass tuning characteristic, whereas the high-level simultaneously masked tuning curve in background noise demonstrates a broad low-pass tuning characteristic. It is argued that comparisons of tuning in impaired ears with tuning in normal ears should be made using estimates of tuning in normal ears that are not influenced by combination-tone or combination-band detection cues.

scholarly journals Mechanistic Characteristics of Double Dominant Frequencies of Acoustic Emission Signals in the Entire Fracture Process of Fine Sandstone

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3959 ◽  
Author(s):  
Chuangye Wang ◽  
Xinke Chang ◽  
Yilin Liu ◽  
Shijiang Chen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Fracture Process ◽  
Low Frequency ◽  
High Amplitude ◽  
Dominant Frequency ◽  
Band Energy ◽  
Ae Signal ◽  
Low Amplitude ◽  
Frequency Band Energy

To determine the intrinsic relationship between the acoustic emission (AE) phenomenon and the fracture pattern pertaining to the entire fracture process of rock, the present paper proposed a multi-dimensional spectral analysis of the AE signal released during the entire process. Some uniaxial compression AE tests were carried out on the fine sandstone specimens, and the axial compression stress–strain curves and AE signal released during the entire fracture process were obtained. In order to deal with tens of thousands of AE data efficiently, a subroutine was programmed in MATLAB. All AE waveforms of the tests were denoised by wavelet threshold firstly. The fast Fourier transform (FFT) and wavelet packet transform (WPT) were applied to the denoised waveforms to obtain the dominant frequency, amplitude, fractal, and frequency band energy ratio distribution. The results showed that the AE signal in the entire fracture process of fine sandstone had a double dominant frequency band of the low and high-frequency bands, which can be subdivided into low-frequency low-amplitude, high-frequency low-amplitude, high-frequency high-amplitude, and low-frequency high-amplitude signals, according to the magnitude. The low-frequency amplitude relevant fractal dimension and the high-frequency amplitude relevant fractal dimension each had turning points that corresponded to significant decreases in the middle and end stages of loading, respectively. The frequency band energy was mainly concentrated in the range of 0–187.5 kHz, and the energy ratios of some bands had different turning points, which appeared before the complete failure of the rock. It is suggested that the multi-dimensional spectral analysis may understand the failure mechanism of rock better.

THE APPLICATION OF AUDIO‐FREQUENCY MAGNETOTELLURICS (AMT) TO MINERAL EXPLORATION

Geophysics ◽  
1973 ◽  
Vol 38 (6) ◽  
pp. 1159-1175 ◽  
Author(s):  
D. W. Strangway ◽  
C. M. Swift ◽  
R. C. Holmer
Keyword(s):  
Narrow Band ◽  
Mineral Exploration ◽  
Broad Band ◽  
Low Frequency ◽  
High Resistivity ◽  
Analog System ◽  
Conductivity Structure ◽  
Magnetotelluric Method ◽  
Audio Range ◽  
Considerable Experience

With the use of frequencies in the audio range, the magnetotelluric method can determine subsurface electrical conductivity structure at depths appropriate for mineral exploration. In 1963, Kennecott initiated a program to determine the feasibility of this technique as a geophysical tool. As opposed to the broad‐band recording and subsequent Fourier analysis commonly utilized in low‐frequency magnetotelluric studies, Kennecott’s AMT instrumentation is a multifrequency, narrow‐band, analog system which yields scalar apparent resistivities. Since the natural source fields at frequencies from 10 hz to about 20 khz are due to thunderstorm energy, the AMT technique is most useful in summertime operation, as is Afmag. Considerable experience in the field has led to useful applications in several problems: (a) uniform sedimentary columns, (b) high‐resistivity cover, and (c) massive, layered sulfides. Although of predictably little assistance in problems relating to disseminated mineralization exploration, deep targets, or areas with low‐resistivity cover, the AMT technique can be useful in defining sharp lateral contrasts in resistivity and in “seeing” through high‐resistivity cover.

Monitoring Seismicity on Mars - the Marsquake Service for InSight

2020 ◽  
Author(s):  
John Clinton ◽  
Domenico Giardini ◽  
Savas Ceylan ◽  
Martin van Driel ◽  
Simon Stähler ◽  
...  
Keyword(s):  
High Frequency ◽  
Body Wave ◽  
A Priori ◽  
Broad Band ◽  
Low Frequency ◽  
Ambient Vibration ◽  
Crustal Layer ◽  
Seismic Waveforms ◽  
Seismic Vibrations ◽  
Back Azimuth

<p>InSight landed on Mars in late November 2018, and the SEIS seismometer package was fully deployed by February 2019. By January 2020, SEIS continues to exceed performance expectations in terms of observed minimum noise. The Marsquake Service (MQS) has been setup to create and curate a seismicity catalogue for Mars over the lifetime of the InSight mission. Seismic waveforms are downloaded daily from the station and are analysed and processed by the MarsQuake Service, with the goal of detecting seismic vibrations not due to local ambient sources. To this end, every precaution is applied to eliminate possible non-seismic sources, such as noise induced by atmospheric phenomena, lander vibrations and orbiter activity. At the date of submission, we have detected 365 events, of different quality and SNR levels. Signal amplitudes remain small and signal can generally only be detected at night. Some events show only low-frequency waves in the 1-10 sec band, others have a high-frequency content up to several Hz, and others have a more broad-band character. A special class of events involves the excitation of a very prominent ambient vibration at 2.4Hz. Despite the scattered nature of the energy, in many cases, distinct phases can be inferred in the waveforms. Body wave character, and back-azimuth, can only be confirmed for 3 broadband events so far.  The MQS approach for determining distances from broadband events identifies phases as mantle P and S-phases and uses an a priori set of several thousand martian models, derived from geophysical, mineralogical and orbital constraints. High frequency events are currently located assuming phases are trapped crustal Pg and Sg and using a simple crustal layer. The MQS works in conjunction with the Mars Structural Service (MSS) on building and adopting updated models. The MQS consists of an international team of seismologists that screen incoming data to identify and characterise any seismicity. In this presentation, we present the MQS, demonstrate how we detect and characterise marsquakes, and describe the challenges we face dealing with the Martian dataset.</p>

Selective loss of high-frequency oscillations in phrenic and hypoglossal activity in the decerebrate rat during gasping

2006 ◽  
Vol 291 (5) ◽  
pp. R1414-R1429 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Power Distribution ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
High Amplitude ◽  
Medial Branch ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Nerve Recordings

Respiratory motor outputs contain medium-(MFO) and high-frequency oscillations (HFO) that are much faster than the fundamental breathing rhythm. However, the associated changes in power spectral characteristics of the major respiratory outputs in unanesthetized animals during the transition from normal eupneic breathing to hypoxic gasping have not been well characterized. Experiments were performed on nine unanesthetized, chemo- and barodenervated, decerebrate adult rats, in which asphyxia elicited hyperpnea, followed by apnea and gasping. A gated fast Fourier transform (FFT) analysis and a novel time-frequency representation (TFR) analysis were developed and applied to whole phrenic and to medial branch hypoglossal nerve recordings. Our results revealed one MFO and one HFO peak in the phrenic output during eupnea, where HFO was prominent in the first two-thirds of the burst and MFO was prominent in the latter two-thirds of the burst. The hypoglossal activity contained broadband power distribution with several distinct peaks. During gasping, two high-amplitude MFO peaks were present in phrenic activity, and this state was characterized by a conspicuous loss in HFO power. Hypoglossal activity showed a significant reduction in power and a shift in its distribution toward lower frequencies during gasping. TFR analysis of phrenic activity revealed the increasing importance of an initial low-frequency “start-up” burst that grew in relative intensity as hypoxic conditions persisted. Significant changes in MFO and HFO rhythm generation during the transition from eupnea to gasping presumably reflect a reconfiguration of the respiratory network and/or alterations in signal processing by the circuitry associated with the two motor pools.

scholarly journals How well are FREQUENCY SENSITIVITIES OF grasshopper ears tuned to species-specific song spectra?

1996 ◽  
Vol 199 (7) ◽  
pp. 1631-1642
Author(s):  
J Meyer ◽  
N Elsner
Keyword(s):  
High Frequency ◽  
Broad Band ◽  
Low Frequency ◽  
Attachment Site ◽  
The Body ◽  
Frequency Range ◽  
Frequency Spectra ◽  
Interspecific Differences ◽  
Tympanal Membrane ◽  
Species Specific

Grasshoppers of 20 acridid species were examined using spectral analysis, laser vibrometry and electrophysiology to determine whether the song spectra, the best frequencies of tympanal-membrane vibrations and the threshold curves of the tympanal nerves are adapted to one another. The songs of almost all species have a relatively broad-band maximum in the region between 20 and 40 kHz and a narrower peak between 5 and 15 kHz. There are clear interspecific differences in the latter, which are not correlated with the length of the body or of the elytra. At the site of attachment of the low-frequency receptors (a-cells), the tympanal membrane oscillates with maximal amplitude in the region from 5 to 10 kHz. At the attachment site of the high-frequency receptors (d-cells), there is also a maximum in this region as well as another around 15-20 kHz. The tympanal nerve is most sensitive to tones between 5 and 10 kHz, with another sensitivity maximum between 25 and 35 kHz. The species may differ from one another in the position of the low-frequency peaks of the membrane oscillation, of the nerve activity and of the song spectra. No correlation was found between the characteristic frequency of the membrane oscillation and the area of the tympanal membrane. Within a given species, the frequency for maximal oscillation of the membrane at the attachment site of the low-frequency receptors and the frequency for maximal sensitivity of the tympanal nerve are in most cases very close to the low-frequency peak in the song spectrum. In the high-frequency range, the situation is different: here, the position of the peak in the song spectrum is not correlated with the membrane oscillation maximum at the attachment site of the high-frequency receptors, although there is a correlation between the song spectrum and the sensitivity of the tympanal nerve. On the whole, therefore, hearing in acridid grasshoppers is quite well adjusted to the frequency spectra of the songs, partly because the tympanal membrane acts as a frequency filter in the low-frequency range.

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