Signal‐to‐noise ratio and time‐modulated signal spectrum in four‐dimensional antenna arrays

2015 ◽  
Vol 9 (3) ◽  
pp. 264-270 ◽  
Author(s):  
Quanjiang Zhu ◽  
Shiwen Yang ◽  
Paolo Rocca ◽  
Zaiping Nie
Keyword(s):  
Antenna Arrays ◽  
Signal To Noise Ratio ◽  
Signal Spectrum ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals A Versatile Analog Electronic Interface for Piezoelectric Sensors Used for Impacts Detection and Positioning in Structural Health Monitoring (SHM) Systems

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1047
Author(s):  
Lorenzo Capineri ◽  
Andrea Bulletti
Keyword(s):  
Lamb Waves ◽  
Signal To Noise Ratio ◽  
Piezoelectric Sensors ◽  
Signal Spectrum ◽  
Signal To Noise ◽  
Front End ◽  
Analog Front End ◽  
Frequency Components ◽  
Noise Ratio ◽  
The Impact

Continuous monitoring of mechanical impacts is one of the goals of modern SHM systems using a sensor network installed on a structure. For the evaluation of the impact position, there are generally applied triangulation techniques based on the estimation of the differential time of arrival (DToA). The signals generated by impacts are multimodal, dispersive Lamb waves propagating in the plate-like structure. Symmetrical S0 and antisymmetrical A0 Lamb waves are both generated by impact events with different velocities and energies. The discrimination of these two modes is an advantage for impact positioning and characterization. The faster S0 is less influenced by multiple path signal overlapping and is also less dispersive, but its amplitude is generally 40–80 dB lower than the amplitude of the A0 mode. The latter has an amplitude related to the impact energy, while S0 amplitude is related to the impact velocity and has higher frequency spectral content. For these reasons, the analog front-end (AFE) design is crucial to preserve the information of the impact event, and at the same time, the overall signal chain must be optimized. Large dynamic range ADCs with high resolution (at least 12-bit) are generally required for processing these signals to retrieve the DToA information found in the full signal spectrum, typically from 20 kHz to 500 kHz. A solution explored in this work is the design of a versatile analog front-end capable of matching the different types of piezoelectric sensors used for impact monitoring (piezoceramic, piezocomposite or piezopolymer) in a sensor node. The analog front-end interface has a programmable attenuator and three selectable configurations with different gain and bandwidth to optimize the signal-to-noise ratio and distortion of the selected Lamb wave mode. This interface is realized as a module compatible with the I/O of a 16 channels real-time electronic system for SHM previously developed by the authors. High-frequency components up to 270 kHz and lower-frequency components of the received signals are separated by different channels and generate high signal-to-noise ratio signals that can be easily treated by digital signal processing using a single central unit board with ADC and FPGA.

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.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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