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Introduction to Nanosensors
Published in Vinod Kumar Khanna, Nanosensors, 2021
In static atomic force microscopy, the imaging signal is given by the DC deflection of the cantilever, which is subject to 1/f noise. Pink noise, or 1/f noise, is a signal or process with a frequency spectrum, such that the power spectral density is inversely proportional to the frequency. In dynamic atomic force microscopy, the low-frequency noise (noise that has a frequency between 20 and 100–150 Hz) is discriminated if the eigenfrequency f0 is larger than the 1/f corner frequency (the frequency at which the 1/f noise spectral density equals the white noise, a random signal or process with a flat power spectral density). With a bandpass filter (an electronic device or circuit that allows signals between two specific frequencies to pass, but rejects or attenuates signals at other frequencies) with a center frequency (midpoint in the pass band) of around f0, only the white noise density is integrated across the bandwidth B of the bandpass filter.
Spectral Analysis
Published in Colin H. Hansen, Foundations of Vibroacoustics, 2018
There are three types of noise signal used in acoustics to excite systems for the purpose of measuring their acoustical properties. White noise, which is a signal with uniform spectral energy (that is, equal energy per Hz). White noise has a flat spectral shape when viewed on a narrow band spectrum, but increases at a rate of 3 dB per octave when viewed on an octave band plot.Pink noise, which is a signal with the same amount of energy in each octave band. Pink noise has a flat spectral shape when viewed on an octave band plot, but has a downwards slope and decreases at 3 dB per octave (doubling of freq) when viewed on a narrow band plot.Pseudo-random noise, which is discussed in Section 7.3.17.Swept sine, which is a single frequency signal that gradually increases in frequency during the measurement process.
Frequency Analysis
Published in David A. Bies, Colin H. Hansen, Carl Q. Howard, Engineering Noise Control, 2018
David A. Bies, Colin H. Hansen, Carl Q. Howard
There are three types of noise signal used in acoustics to excite systems for the purpose of measuring their acoustical properties. White noise, which is a signal with uniform spectral energy (that is, equal energy per Hz). White noise has a flat spectral shape when viewed on a narrow band spectrum, but increases at a rate of 3 dB per octave when viewed on an octave band plot.Pink noise, which is a signal with the same amount of energy in each octave band. Pink noise has a flat spectral shape when viewed on an octave band plot, but has a downwards slope and decreases at 3 dB per octave (doubling of freq) when viewed on a narrow band plot.Pseudo-random noise, which is discussed in Section 12.3.17.Swept sine, which is a single frequency signal that gradually increases in frequency during the measurement process.
Neural network-based multi-view enhanced multi-learner active learning: theory and experiments
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2022
The testing data were infected with additive noise to measure the robustness of the proposed model against noise. The noise profiles were selected from three coloured frequency-based noises: white, pink, and brown noises. Such noise profiles are among the most common environmental noise profiles: White noise propagates itself as a gentle hiss, such as the noise created by air conditioning systems. It has a constant power spectral density (i.e., it has relatively similar frequencies).Pink noise propagates itself as more subdue and softer than white noise. It has a power spectral density that dwindles inversely in proportion to the frequency. In pink noise, low acoustic frequencies are louder than higher acoustic frequencies. On the sound frequency spectrum, it is located between white and brown noise profiles. An example would be an empty television channel generating a buzz.Among the three noise profiles, brown noise is the softest and dampest, where lower frequencies have the highest energy. It is also known as drunkard’s walk or random, such as vibrations generated by machinery.
Speech intelligibility test methodology applied to powered air-purifying respirators used in healthcare
Published in Journal of Occupational and Environmental Hygiene, 2020
Susan Xu, Jeremy Simons, Patrick Yorio, Dana Rottach, Ziqing Zhuang, Lewis Radonovich
Tests were conducted in a hemi-anechoic chamber, measuring approximately 33 × 55 ft (10 × 16.8 m) at NIOSH/NPPTL (Pittsburgh, PA). The listeners sat in a line spaced 1 foot apart, with the center listener directly in front of the speaker, seated a distance of 10 ft (3 m) away (Figure 2). Nine feet on either side of the midpoint line between the listeners and the speaker, 20–50 Hz pink noise was generated by a Precision Pink Noise Generator (PNG) (GTC Industries, NC MX-Neutrik, Indianapolis, IN). The amplitude of the pink noise was adjusted to 60 dB +/- 2 dBA, measured by two type-2 digital sound meters (Sper Scientific LTD, Model 840029, Scottsdale, AZ). One sound level meter was positioned in front of the speaker and the second sound level meter was positioned at head level 1 foot in front of the center listener. An Acoustical Calibrator (Sper Scientific LTD, model 840031, Scottsdale, AZ) was used to calibrate the sound level meters.
An inexpensive sensor for noise
Published in Journal of Occupational and Environmental Hygiene, 2018
Laura Hallett, Marcus Tatum, Geb Thomas, Sinan Sousan, Kirsten Koehler, Thomas Peters
The sound pressure levels measured with 50 noise sensors embedded within the larger monitors were compared to those measured with an SLM (XL2 Audio and Acoustic Analyzer, NTi Audio, Tigard, OR, USA) (Figure 2). Each noise sensor was tested individually inside a quiet office. The microphones of the SLM and noise sensor were placed within 2.5 cm of each other and 30 cm from the center of a guitar amplifier (Fender Musical Instruments Corporation, Frontman 10G, Scottsdale, AZ, USA). The amplifier was connected to a laptop computer with an auxiliary cord. Five target sound levels, ambient, 65 dBA, 75 dBA, 85 dBA, and 94 dBA, were generated to test each noise sensor. These sound levels were adapted from the range used by Kardous and Shaw in their evaluation of smartphone applications and to meet our needs to measure noise in a heavy-vehicle manufacturing facility. For levels from 65–85 dBA, pink noise was produced by playing a computer sound file (NTi Audio Test Signals for Audio and Acoustic Analyzers V1.0) through the guitar amplifier. The sound level was adjusted using the volume settings on the laptop and then verified on the reference SLM before each testing period began. The 94-dBA tone was generated using a sound level calibrator (General Tools & Instruments, SCAL1356, Secaucus, NJ, USA). Each test tone was generated for 30 sec before moving on to the next. Both the noise sensor and SLM reported 1 sound pressure level measurement every 2 sec over each 30-sec testing period, n = 50 sensors × 5 test levels × 1 measurement every 2 sec × 30 sec = 3,750 paired measurements.