Electronic Acoustic Sensor

2005 ◽  
Vol 889 ◽  
Author(s):  
Vivek Bharti ◽  
Fred L. DeRoos
Keyword(s):  
Medical Equipment ◽  
Signal To Noise Ratio ◽  
Piezoelectric Sensor ◽  
Acoustic Sensor ◽  
Differential Mode ◽  
Signal To Noise ◽  
Remote Areas ◽  
Primary Health ◽  
Electronic Amplifier ◽  
Diagnosis Of Diseases

AbstractThe Stethoscope (acoustic sensor) is a fundamental tool for the diagnosis of diseases and conditions of the cardiovascular (CV) system. It serves as the most commonly employed technique for diagnosis of such diseases and conditions in primary health care and in circumstances where sophisticated medical equipment is not available, such as remote areas. The piezoelectric sensor was used as an acoustic sensor. The sensitivity of the sensor was improved more than 20 times with our new design. The signal-to-noise ratio was further improved by using unique sensor housing and by using an electronic amplifier in the differential mode.

Study on the Surface Roughness of Titanium Alloy Machined by WEDM

2013 ◽  
Vol 683 ◽  
pp. 581-584 ◽  
Author(s):  
Shu Guo Zhao ◽  
Rui Li ◽  
Xiao Min Yao
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Electrical Discharge ◽  
Medical Equipment ◽  
Electrical Discharge Machining ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Relational Analysis ◽  
Electric Parameters ◽  
Grey Relational

Due to the excellent characteristics of titanium alloy, was applied to aviation, marine, automotive, metallurgy, medical equipment and other fields. However, some of the characteristics make it machine difficultly, so the range of applications would be limited. In this paper, titanium alloy is cut by wire electrical discharge machining (WEDM) and study the surface finish. The model of surface roughness is established which is based on theoretical analysis. Experimental results were analyzed and optimized by the theory of signal-to-noise ratio and grey relational analysis (GRA) method. The minimal surface roughness is achieved by the optimal results .According to GRA, get the order that is the influence of electric parameters on the surface roughness.

scholarly journals Normalized differential method for improving the signal-to-noise ratio of a distributed acoustic sensor

2019 ◽  
Vol 58 (18) ◽  
pp. 4933 ◽  
Author(s):  
Islam Ashry ◽  
Yuan Mao ◽  
Mohd Sharizal Alias ◽  
Tien Khee Ng ◽  
Frode Hveding ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Differential Method ◽  
Acoustic Sensor ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Numerical Modelling of a Distributed Acoustic Sensor Based on Ultra-Low Loss-Enhanced Backscattering Fibers

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6869
Author(s):  
Lieke Dorine van van Putten ◽  
Ali Masoudi ◽  
James Snook ◽  
Gilberto Brambilla
Keyword(s):  
Numerical Modelling ◽  
Signal To Noise Ratio ◽  
Single Mode ◽  
Acoustic Sensor ◽  
Low Loss ◽  
Signal To Noise ◽  
Optical Components ◽  
Enhanced Backscattering ◽  
Noise Ratio

In this study, a distributed acoustic sensor (DAS) was numerically modeled based on the non-ideal optical components with their noises and imperfections. This model is used to compare the response of DAS systems to standard single-mode fibers and ultra-low loss-enhanced backscattering (ULEB) fibers, a fiber with an array of high reflective points equally spaced along its length. It is shown that using ULEB fibers with highly reflective points improves the signal-to-noise ratio and linearity of the measurement, compared with the measurement based on standard single-mode fibers.

Improving the signal-to-noise ratio in a fiber-optic Fabry–Pérot acoustic sensor

2019 ◽  
Vol 16 (6) ◽  
pp. 065106 ◽  
Author(s):  
Hamed Moradi ◽  
Fahimeh Hosseinibalam ◽  
Smaeyl Hassanzadeh
Keyword(s):  
Fiber Optic ◽  
Signal To Noise Ratio ◽  
Acoustic Sensor ◽  
Signal To Noise ◽  
Fabry Perot ◽  
Noise Ratio

scholarly journals Detection of Pathologic Heart Murmurs Using a Piezoelectric Sensor

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1376
Author(s):  
Kiichi Takahashi ◽  
Kyoichi Ono ◽  
Hirokazu Arai ◽  
Hiroyuki Adachi ◽  
Masato Ito ◽  
...  
Keyword(s):  
Congenital Heart Defects ◽  
Congenital Heart ◽  
Signal To Noise Ratio ◽  
Heart Defects ◽  
Piezoelectric Sensor ◽  
Heart Murmur ◽  
Signal To Noise ◽  
Electronic Stethoscope ◽  
Heart Murmurs ◽  
High Pass

This study aimed to evaluate the capability of a piezoelectric sensor to detect a heart murmur in patients with congenital heart defects. Heart sounds and murmurs were recorded using a piezoelectric sensor and an electronic stethoscope in healthy neonates (n = 9) and in neonates with systolic murmurs caused by congenital heart defects (n = 9) who were born at a hospital. Signal data were digitally filtered by high-pass filtering, and the envelope of the processed signals was calculated. The amplitudes of systolic murmurs were evaluated using the signal-to-noise ratio and compared between healthy neonates and those with congenital heart defects. In addition, the correlation between the amplitudes of systolic murmurs recorded by the piezoelectric sensor and electronic stethoscope was determined. The amplitudes of systolic murmurs detected by the piezoelectric sensor were significantly higher in neonates with congenital heart defects than in healthy neonates (p < 0.01). Systolic murmurs recorded by the piezoelectric sensor had a strong correlation with those recorded by the electronic stethoscope (ρ = 0.899 and p < 0.01, respectively). The piezoelectric sensor can detect heart murmurs objectively. Mechanical improvement and automatic analysis algorithms are expected to improve recording in the future.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

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