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The noise measurement on magnetoresistive (MR) sensors is generally conducted by techniques including single-channel data sampling and fast Fourier transform (FFT) analysis as well as two-channel cross-correlation. The single-channel method is easy to implement and is widely used in the noise measurement on MR sensors, whereas the two-channel method can only eliminate part of the system noise. This study aims to address two key issues affecting measurement accuracy: calibration of the measurement system and the elimination of system noise.

The system is calibrated by using a low-noise metal film resistor in that the system noise is eliminated through power spectrum subtraction. Noise measurement and analysis are conducted for both thermal noise and detectivity of magnetic tunnel junction (MTJ) sensor.

The thermal noise measurement error is less than 2%. The detectivity of the MTJ sensor reaches 27 pT/Hz^1/2 at 2 kHz.

This study provides a more practical solution for noise measurement and system calibration on MR sensors with a bias voltage and magnetic field.

This paper aims to propose and demonstrate novel microphone sensors based on the frequency delta-sigma modulation (FDSM) technique, which replaces the conventional delta-sigma modulator in the delta-sigma analog-to digital converters. A key of the FDSM technology is to use a voltage-controlled oscillator (VCO) for converting an input analog signal to a 1-bit pulse-density modulated digital signal. High-performance sensors can be realized if the VCO is replaced by an oscillator whose oscillation frequency depends on an external physical parameter.

Microphone sensors are proposed based on FDSM that uses a suspended microstrip disk resonator, where the backside ground plane is replaced by a thin metal diaphragm. A resonant tunneling diode (RTD) oscillator is also used, as the performance of these sensors significantly depends on the oscillation frequency. To demonstrate the basic operation of the proposal, prototype devices were fabricated with an InGaAs/AlAs RTD.

A satisfactory noise shaping property, which is a significant nature of delta-sigma modulation, was demonstrated over three decades for the prototype device. A sound-sensing peak was also clearly observed when applying 1 kHz sound from a speaker.

High-performance ultrasonic microphone sensors can be realized if the sensors are fabricated by using a thin InP substrate with high-frequency oscillator design.

In this study, the authors proposed and experimentally demonstrated novel microphone sensors, which are promising as future ultrasonic sensors that have high dynamic range with wide bandwidth.

THE vast majority of noise specifications, rating indices, requlations and working procedures are based around overall levels and/or octave or fractional octave frequency analysis. Traditionally, analyses of this type are carried out by passing noise signals through analogue filter sets, using the ‘energy’ (pressure‐squared) outputs that result to drive analogue or digital indicators.

This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

The objective of this paper is to provide a brief review of recent developments in the area of applications of ANN, Fuzzy Logic, and Wavelet Transform in fault diagnosis. The purpose of this work is to provide an approach for maintenance engineers for online fault diagnosis through the development of a machine condition‐monitoring system.

A detailed review of previous work carried out by several researchers and maintenance engineers in the area of machine‐fault signature‐analysis is performed. A hybrid expert system is developed using ANN, Fuzzy Logic and Wavelet Transform. A Knowledge Base (KB) is created with the help of fuzzy membership function. The triangular membership function is used for the generation of the knowledge base. The fuzzy‐BP approach is used successfully by using LR‐type fuzzy numbers of wavelet‐packet decomposition features.

The development of a hybrid system, with the use of LR‐type fuzzy numbers, ANN, Wavelets decomposition, and fuzzy logic is found. Results show that this approach can successfully diagnose the bearing condition and that accuracy is good compared with conventionally EBPNN‐based fault diagnosis.

The work presents a laboratory investigation carried out through an experimental set‐up for the study of mechanical faults, mainly related to the rolling element bearings.

The main contribution of the work has been the development of an expert system, which identifies the fault accurately online. The approaches can now be extended to the development of a fault diagnostics system for other mechanical faults such as gear fault, coupling fault, misalignment, looseness, and unbalance, etc.

Now available from Schlumberger Instruments is a new brochure for the SI 1202 Structural Analyser.

The purpose of this paper is to inspect strategic placing of different signal processing techniques like wavelet transform (WT), discrete Hilbert transform (DHT) and fast Fourier transform (FFT) to acquire the qualitative detection of rotor fault in a variable frequency drive-fed induction motor under challenging low slip conditions.

The algorithm is developed using Q2.14 bit format of Xilinx System Generator (XSG)-DSP design tool in MATLAB. The developed algorithm in XSG-MATLAB can be implemented easily in field programmable gate array, as a provision to generate the necessary VHDL code is available by its graphical user interface.

The applicability of WT is ensured by the effective procedure of base wavelet selection, which is the novelty of the work. It is found that low-order Daubechies (db) wavelets show decent shape matching with current envelope rather than raw current signal. This fact allows to use db1-based discrete wavelet transform-inverse discrete wavelet transform, where economic and multiplier-less design is possible. Prominent identity of 2sf_s component is found even at low FFT points due to the application of suitable base wavelet.

The proposed method is found to be effective and hardware-friendly, which can be used to design a low-cost diagnostic instrument for industrial applications.

Microstereolithography is capable of producing millimeter-scale polymer parts having micron-scale features. Material properties of the cured polymers can vary depending on build parameters such as exposure. Current techniques for determining the material properties of these polymers are limited to static measurements via micro/nanoindentation, leaving the dynamic response undetermined. The purpose of this paper is to demonstrate a method to measure the dynamic response of additively manufactured parts to infer the dynamic modulus of the material in the ultrasonic range.

Frequency-dependent material parameters, such as the complex Young’s modulus, have been determined for other relaxing materials by measuring the wave speed and attenuation of an ultrasonic pulse traveling through the materials. This work uses laser Doppler velocimetry to measure propagating ultrasonic waves in a solid cylindrical waveguide produced using microstereolithography to determine the frequency-dependent material parameters of the polymer. Because the ultrasonic wavelength is comparable with the part size, a model that accounts for both geometric and viscoelastic dispersive effects is used to determine the material properties using experimental data.

The dynamic modulus in the ultrasonic range of 0.4-1.3 MHz was determined for a microstereolithography part. Results were corroborated by using the same experimental method for an acrylic part with known properties and by evaluating the natural frequency and storage modulus of the same microstereolithography part with a shaker table experiment.

The paper demonstrates a method for determining the dynamic modulus of additively manufactured parts, including relatively small parts fabricated with microstereolithography.

This paper aims to estimate the corrosion rate of the carbon steel in crude oil using the electrochemical noise (EN) analysis technique.

EN measurements and electrochemical impedance (EIS) spectroscopy were employed to study the corrosion behaviour of carbon steel in crude oil and the optimum conditions of the noise analysis for estimating corrosion rate of the carbon steel are discussed. The time series noise patterns were transformed into frequency domains by fast Fourier transformation, and then their power spectrum densities (PSDs) at a frequency were determined to be compared with the corrosion rate.

The PSDs of the potential and of the current varied with changing of rotation rate of electrode and immersion time. Square roots of the PSDs for the potential difference and for the currents were in positive and almost linear correlation with the corrosion rate obtained from EIS plots. In addition, the spectral noise was negatively and linearly correlated with the corrosion rate. The relationship between the corrosion rate and the spectral noise resistance was better at lower frequencies.

It is suggested that this research is carried out for crude oils with other physical and chemical characteristics.

The PSD value at 3 mHz from the noise of the current and the spectral noise resistance at the same frequency are the optimum conditions for estimating corrosion rate in this research.

This paper arguably fills a gap in the current understanding of the interactions between corrosive species commonly found in crude feedstocks and process streams.

A binaural sonar sensor for blind persons which models the bat sonar is described. System performance with field plots are presented along with signal analysis on objects forming targets. The distal spatial resolution is little more than one wavelength at the lowest frequency of 50 kHz. The operating bandwidth is 50 kHz producing the power to discriminate between objects. Distance and direction information is obtained over a field of view of 50 degrees within one frequency sweep. Blind persons have demonstrated mobility akin to sighted mobility. This knowledge is of value in designing robots.