Frequency Background Noise Research Articles

An analysis and retrofit of the acoustics at Image Creators Health and Beauty Salon

This paper discusses the analysis and retrofit of the acoustics in a high-volume beauty salon in Severna Park, Md. The major issues in what was intended to be a serene environment are reverberation times of 1–1.68 s in the mid-to upper frequency range and Background noise levels ranging from 73.4 to 64.6 dB in the mid to low frequency range. Employee and customer complaints include ear pain and tinnitus due to prolonged exposure to high background levels, heightened stress, vocal strain, headaches and poor speech intelligibility. Existing analysis and the acoustical retrofit resolution will be demonstrated.

Cataluminescence sensor based on LaCO3OH microspheres for volatile organic compounds detection and pattern recognition

The cataluminescence (CTL) reaction detects the presence and concentration of toxic volatile organic compounds by detecting the luminescence intensity of the different components of the gas mixture. In our study, a cataluminescence online sensor system based on LaCO3OH microspheres was developed for the low concentration detection of volatile organic compounds. Multi-dimensional CTL test was carried out to analyse the correlation characteristics of heterogeneous analytes among the catalytic activity, selectivity, sensitivity, response/recover time, stability, and photoelectric signals by changing the parameters of wavelength, flow rate, temperature, and response time under the optimal conditions (280 mL/min, 180ºC, and 480 nm). Due to noise interference received by the CTL signal, the weak CTL signal was filtered based on the time-frequency characteristics of the CTL pattern signal power frequency interference and background noise. Next, this study also studied the mechanism action of the cataluminescence sensor based on LaCO3OH microspheres for gas detection, including ethyl ether, acetone, chloroform, and formaldehyde. The principal component analysis (PCA) algorithm was adopted to analyse the CTL patterns, after threshold filtering, the total variance was improved from 89.23% to 98.78% and each vapour gave its unique CTL patterns. Moreover, clustering and identification are discussed to analyse the results, including Hierarchical Cluster Analysis (HCA) and Radial Basis Function Neural Networks (RBFNN), was also discussed. The excellent cluster and recognition ability indicate the feasibility of this CTL sensor for volatile compound determination.

Bearing Fault Diagnosis usingEnhanced Envelope Analysis

Early fault detection and diagnosis of bearing is of paramount importance in wind turbines as it contributes to around 70% of gearbox and 21%-70% of generator failure. This paper presents an enhanced envelope analysis technique for bearing fault identification using vibration measurements. The raw vibration signal measured from the outer casing of the WT gearbox with faulty bearing has not only fault frequency component but also resonant frequency, discrete frequency (gear and shaft) and high frequency background noise. The present work diagnose bearing faults through a three-step process: i) using Auto- Regressive(AR) time series model to remove discrete frequency components of gear and shaft ii) fault-sensitive frequency and demodulation band selection using spectral kurtosis. The spectral kurtosis is expected to higher around the region of resonance frequencies when fault occurs otherwise the fault signal is modulated. iii) envelope analysis to obtain spectrum by Hilbert Transform (HT) and retrieval of fault information. The order of the AR model is chosen such that the residual signal exhibits maximum kurtosis and spectral kurtosis is computed through short time Fourier Transform (STFT). The enhanced envelope analysis technique for bearing fault diagnosis is verified and validated using numerical simulations and Korea Aerospace University bearing damage benchmark datasets.

Study of weld pool monitoring system based on spatial filtering

The observable information of the welding process mainly includes the weld pool, weld seam, and arc length, which can be used to predict the penetration depth, perform weld tracking, and provide early warning of weld defects. Welding monitoring technology based on machine vision has been widely researched to improve the quality and efficiency of welding. This paper proposes a novel weld pool image acquisition system based on spatial filtering and Abbe’s theory of image formation. A high-pass spatial filter was designed to eliminate the low frequency background noise so that the contour of the weld pool, weld seam, and arc shape were acquired. Compared with the weld pool monitoring system based on an optical filter, this method more effectively solved the problem of the large radiation gradient in the weld pool area, and the weld pool could be more clearly observed. It provided a new method to image the weld pool image system with the advantages of low cost and ease of implementation.

DNLS: A Detection Method Based on Normalized Short-Time Fourier Transform-Radon Transform for Low Frequency Sonar Pulse Signal

Under low-frequency background noise environments, due to the characteristics of poor stability and many interference targets of noise, the detection of unknown low-frequency sonar signals faces huge challenge. And sonar pulse signal detection methods based on time domain or frequency domain have the limitation of insufficient detection Signal-to-Noise Ratio (SNR). In order to improve the detection capability of weak sonar pulse signal in low frequency background noise environments, a Detection method based on normalized short-time Fourier transform-Radon transform for Low frequency Sonar pulse signal (DNLS) is proposed, which is a constant false alarm detection method in normalized short-time Fourier transform-Radon transform domain. In DNLS method, after the normalized short-time Fourier transform-Radon transformation, low-frequency noise energy to be dispersed into the entire transformation domain, and the sonar pulse signal energy containing the Linear Frequency Modulation (LFM) component is concentrated at a specific target point in the normalized short-time Fourier transform-Radon transform transformation domain, which can obtain a higher local SNR than the time-domain SNR. Moreover, the specific target point is distinguishable from the background noise, and the impulse signal detection decision is completed by constructing hypothesis test statistics on the target point data. The DNLS method solves the detection problems of low-frequency background such as poor stability, large fluctuations, and more interference. And the method of obtaining the test statistics of the constant false alarm detection, estimating the background noise and calculating the detection threshold is given. Extensive simulation results and actual data processing show that, under the simulation condition, in the minimum detection SNR of LFM, Continuous Wave(CW)-LFM and pulse trains of frequency modulated pulse signals with the same pulse width, compared with the dual-threshold constant false alarm rate energy detection method, the DNLS method is improved by 15dB, 13dB and 4dB, respectively. Under actual data conditions, in the detection of CW-LFM pulse signals with the same pulse width, compared with the double-threshold constant false alarm rate energy detection method, the detection performance of the DNLS method in the case of no ship radiated noise interference and strong radiated noise interference improves by 5dB and 5.5dB, respectively. The data analysis results show that the DNLS method has very good detection performance for LFM, pulse trains of frequency modulated, CW-LFM and other sonar pulse signals at low SNR, and can effectively detect the sonar pulse signals under the background of strong ship radiated noise.

Series Arc Fault Detection of Grid-Connected PV System via SVD Denoising and IEWT-TWSVM

Series arc fault (SAF) is one of the most harmful faults during the operation of photovoltaic (PV) systems. It is a challenging task to find SAFs promptly for avoiding the PV fire. Aiming at the SAFs under different operating conditions, a novel detection algorithm by combining the Hankel singular value decomposition (Hankel-SVD) denoising method and the improved empirical wavelet transform–twin support vector machine (IEWT-TWSVM) is proposed. The Hankel-SVD algorithm is used to denoise the dc-bus current, which alleviates the influence of switching frequency and irrelevant background noise effectively. Then, the denoised current is decomposed by the IEWT, and the composite multiscale permutation entropy of each frequency band is input into the TWSVM classifier of the salp swarm optimization for completing the fault detection. The proposed algorithm not only can detect SAFs at various fault locations, but also resist dynamic shading, inverter startup, strong wind, and other interference phenomena. Moreover, the detection performance due to the arc transient process, a long-line fault, a single string array fault, a multiply string array fault, and different sampling rates of this model is verified in this study, and the corresponding results are relatively ideal. Experimental results show that the detection accuracy of the proposed method is as high as 98.10% for the measured data, which is more superior than other methods, such as wavelet decomposition, empirical mode decomposition, statistics methods including mean, standard deviation, and entropy.

Design of a flagship studio suite for a major recording arts educational program

The architectural acoustic design of a studio, isolation booth and control room as well as an intimate performance hall for amplified music was undertaken for a major recording arts educational program. The university which already has many recording studios, considered this facility as their “Audio Temple” or the showpiece of the entire campus. Acoustical design criteria for reverberation time, low frequency sound control, room response, diffuseness, background noise and sound isolation were established in conjunction with the faculty who will use the spaces. There are classroom spaces above the studio suite and mechanical equipment located near-by, so sound isolation design was an important part of the design effort. A three-layer sound isolation system was used for each of the rooms. The faculty had specific requirements for the interior acoustical qualities of the rooms. The paper presents comparisons of the rooms as designed with the criteria for acoustical quality described by the users for reverberation, low frequency sound, room response, diffuseness and background noise. Efforts were maintained during design and construction to preserve these qualities through the realities of the value engineering and construction process.

Transformation of a warehouse into a professional production studio

A major film production studio was slated for demolition due to the expansion of a theme park. Audio tracks for many popular films and animated productions were designed, recorded and mixed in the facility. Space for the new studio was included in a large office renovation project that was occurring in several large existing warehouse/office buildings. The acoustical challenges of providing sound isolation between and among adjacent recording, control and editing spaces as well as between the studios and the exterior which included building box-in-box-in-box isolation systems within the existing warehouse posed an interesting challenge. With the unforgiving structural system of the existing warehouse building, thinking both outside and inside of the box was necessary. Fitting the low velocity ductwork in the relatively low ceiling height of the existing structure was not easily accomplished. Each of the existing limitations of the warehouse building was overcome by closely working with the Design Team and the Contractor. Acoustical shaping and finish materials were designed and selected to meet the criteria of the users for reverberation, room response, low frequency sound control, diffuseness and background noise. The users were pleased to work in a studio that allowed the artists and the engineers to work throughout the day into the night and through thunderstorms. The studio has been very well-received by the users, since the resulting sound tracks translated very well when played back in a variety of venues.

Singing under glass: rapid effects of anthropogenic habitat modification on song and response behaviours in an isolated house sparrow Passer domesticus population

Anthropogenic noise pollution and the introduction of novel infrastructure can impose strong selective pressures on avian communication by affecting the efficacy with which acoustic signals are transmitted and received. Many species have now been shown to sing at higher frequencies in noisy urban environments. However, few studies have investigated the effects of signal modification on the response behaviours of receivers, and fewer still have been able to indicate the timescale over which these changes in pitch have occurred. We compare vocal communication between house sparrows Passer domesticus that reside within the world's largest, single‐span glasshouse (completed in the year 2000), and house sparrows directly outside this glasshouse, in open farmland. The glasshouse contrasts both acoustically and physically with the external environment, low frequency background noise being significantly louder inside than outside. We show that minimum song frequency was significantly higher inside the glasshouse than in surrounding farm habitat. Using song playback, we also found that birds within the glasshouse reacted more strongly to playbacks from the glasshouse habitat than they did to playback of song from farm birds outside. The degree of difference in frequency is similar to that shown for other bird species between urban and rural environments, demonstrating that such behavioural differences may arise over a relatively short time period (14 yr in this case).

Evaluation Method for Complex Electromagnetic Environment

To perform a complexity evaluation for an electromagnetic environment (EME), a new method based on the S-transform is proposed, which can simultaneously count the time occupancy, frequency occupancy, and energy occupancy in the time–frequency domain. The frequency coincidence, modulation similarity, and background noise intensity are selected as important evaluation indices, and their physical interpretations are analyzed and calculated. The Extreme Learning Machine (ELM) method is adopted to evaluate the environmental complexity. The proposed method (S-ELM) requires less training time and has a fast convergence rate. The simulation and experimental results confirm that the proposed method is accurate and efficient.

Measuring the dynamic stiffness of resilient materials using ESS and MLS signals

Resilient materials are used to reduce vibration transmission in buildings, e.g. in floating floors designed to decrease the impact sound pressure level in the room below the floor. The performance of a floating floor can be estimated in advance knowing the dynamic stiffness per unit area of the resilient material, which is usually measured on a small sample according to ISO 9052-1. Thus, the reliability of results from ISO 9052-1 measurements is crucial. However, the published standard gives few indications on the measuring equipment and suggests measuring the resonance frequency of the fundamental vertical vibration of the test specimen and of the load plate by using either sinusoidal, white noise or pulse signals, considered as equivalent. In this work, a measuring apparatus following the ISO 9052-1 specifications with some hardware and software improvements is described. Then the scanty specifications about the excitation signal are complemented introducing two robust alternatives, compatible with the ISO 9052-1 prescriptions: the ESS (Exponential Swept Sine) and MLS (Maximum Length Sequence) signals. The two newly proposed signals are validated measuring the dynamic stiffness per unit area of different resilient materials, whose resonance frequency is estimated using the same measuring equipment and four different excitation methods: hammer generated impulses, white noise, ESS and MLS. The comparison shows that ESS and MLS signals, already in use since many years for other kinds of acoustic measurements, are viable alternatives to traditional techniques and may have advantages in term of repeatability, dynamic range, cleanness of the frequency response and background noise immunity.

The gap-prepulse inhibition deficit of the cortical N1-P2 complex in patients with tinnitus: The effect of gap duration

The present study aimed to investigate whether gap-prepulse inhibition (GPI) deficit in patients with tinnitus occurred in the N1-P2 complex of the cortical auditory evoked potential. Auditory late responses to the intense sound of the GPI paradigm were obtained from 16 patients with tinnitus and 18 age- and hearing loss-matched controls without tinnitus. The inhibition degrees of the N1-P2 complex were assessed at 100-, 50-, and 20-ms gap durations with tinnitus-pitch-matched and non-matched frequency background noises. At the 20-ms gap condition with the tinnitus-pitch-matched frequency background noise, only the tinnitus group showed an inhibition deficit of the N1-P2 complex. The inhibition deficits were absent in both groups with longer gap durations. These findings suggested that the effect of tinnitus emerged depending on the cue onset timing and duration of the gap-prepulse. Since inhibition deficits were observed in both groups at the same 20-ms gap condition, but with the tinnitus-pitch-non-matched frequency background noise, the present study did not offer proof of concept for tinnitus filling in the gap. Additional studies on the intrinsic effects of different background frequencies on the gap processing are required in the future.

Dual multi-scale filter with SSS and GW for infrared small target detection

Multi-scale analysis is a powerful tool in the field of signal processing. In this paper, we propose an efficient small target detection algorithm that is mainly based on the dual multi-scale filters which work sequentially. The algorithm consists of two stages: at the first stage, Spectrum Scale-Space (SSS) is used as the pre-process procedure to obtain the multi-scale saliency maps, which can suppress the low frequency background noise and make the target region prominently at different scale levels. As a result, the more detail information and feature information can be exhibited in the different decomposition image level. After then, the least information entropy is used as the criterion to select the optimal salient map out; At the second stage, the Gabor wavelets (GW) algorithm is utilized to suppress the high frequency noise remained in the optimal salient map and match the feature of size and direction of small target at different scales and angles, and next, to ensure the robustness of the target detection, Non-negative Matrix Factorization (NMF) is applied to fuse all the GW multi-scale images into one optimal target image, which is the final output of the presented method. Experimental results show that, compared with the contrast method, the proposed algorithm has high SCRG and high correct target detection rate, and works well in different types of complex backgrounds.

Application of Self-Adaptive Wavelet Ridge Demodulation Method Based on LCD to Incipient Fault Diagnosis

When a local defect occurs in gearbox, the vibration signals present as the form of multicomponent amplitude modulation and frequency modulation (AM-FM). Demodulation analysis is an effective way for this kind of signal. A self-adaptive wavelet ridge demodulation method based on LCD is proposed in this paper. Firstly, multicomponent AM-FM signal is decomposed into series of intrinsic scale components (ISCs) and the special intrinsic scale component is selected in order to decrease the lower frequency background noise. Secondly, the genetic algorithm is employed to optimize wavelet parameters according to the inherent characteristics of signal; thirdly, self-adaptive wavelet ridge demodulation wavelet for the selected ISC component is performed to get instantaneous amplitude (IA) or instantaneous frequency (IF). Lastly, the characteristics frequency can be obtained to identify the working state or failure information from its spectrum. By two simulation signals, the proposed method was compared with various existing demodulation methods; the simulation results show that it has higher accuracy and higher noise tolerant performance than others. Furthermore, the proposed method was applied to incipient fault diagnosis for gearbox and the results show that it is simple and effective.

Present Status of the Nd:YAG Thomson Scattering System Development for Time Evolution Measurement of Plasma Profile on Heliotron J

A new high repetition rate Nd:YAG Thomson scattering system is developed for the Heliotron J helical device. A main purpose of installing the new system is the temporal evolution measurement of a plasma profile for improved confinement physics such as the edge transport barrier (H-mode) or the internal transport barrier of the helical plasma. The system has 25 spatial points with ∼10 mm resolution. Two high repetition Nd:YAG lasers (> 550 mJ@50 Hz) realize the measurement of the time evolution of the plasma profile with ∼10 ms time intervals. Scattered light is collected by a large concave mirror (D = 800 mm, f/2.25) with a solid angle of ∼100 mstr and transferred to interference filter polychromators by optical fiber bundles in a staircase form. The signal is amplified by newly designed fast preamplifiers with DC and AC output, which reduces the low frequency background noise. The signals are digitized with a multi-event QDC, fast gated integrators. The data acquisition is performed by a VME-based system operated by the CINOS.

Transform domain methods for performance enhancement of EFPI sensor

The paper presents advances in the processing technique based on transform domain methods for performance enhancement of extrinsic Fabry–Perot interferometric (EFPI) sensors. The paper introduces a new technique to estimate the cavity length from the instantaneous phase. Pre-processing of the EFPI spectrum signal is proposed using wavelet transform to filter out the low frequency background and broadband measurement noise. The filtering technique efficiently extracts the required interference spectrum in a low cavity length EFPI. The computation of the analytic representation of the spectrum signal has been carried out using Hilbert transform. The variation computed using the proposed algorithm in a continuous test with an EFPI of cavity length 66μm is found to be as low as ±1.13nm. The range of wavelength used for processing the EFPI signal for accurate estimation of cavity length also needs to be optimized. In this regard, a definite relation between the wavelength range and cavity length measurement stability have been found. Optimization improves sensor response time and multiplexing ability.

Background removal from polarized Raman spectra of tooth enamel using the wavelet transform

AbstractA wavelet transformation method is introduced to remove the large fluorescence background from polarized Raman spectra of stained tooth enamel. This method exploits the wavelet multiresolution decomposition where the experimental Raman spectrum is decomposed into signals with different frequency components, and where the lowest frequency background and highest frequency noise are removed. This method is optimized using a simulated collection of parallel‐polarized and cross‐polarized Raman spectra of the enamel and then applied to a set of experimental data. The results show that the wavelet transform technique can extract the pure spectra from background and noise, with the depolarization ratio used to discriminate between early dental caries and sound enamel preserved. Copyright © 2010 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

Frequency response, acoustic impedance and background noise of microbarometers.

Frequency response and background noise of microbarometers are derived from their principle of operation. Lumped element models are proposed to describe each part of these absolute infrasound sensors and are used to derive analytical expressions for frequency response, acoustic impedance, and background noise of microbarometers. A set of experimental methods to estimate all elements is discussed in this paper. Some of them need a specific instrumentation developed in our laboratories. Others are very simple as they require only common equipment and can be applied on field to calibrate these sensors. All these methods have been applied to a set of MARTEC MB2005 microbarometers. Results from the theory and measurements are compared in this paper.

Active Noise Reduction Audiometry: A Prospective Analysis of a New Approach to Noise Management in Audiometric Testing

To develop a new method of screening audiometry that reduces the adverse effects of low frequency background noise by using active noise reduction (ANR) headphone technology. Prospective testing within an anechoic chamber evaluated the physical properties of ANR headphones. A prospective clinical crossover study compared standard audiometry with ANR headphone audiometry. Bose Aviation X circum-aural ANR headphones were tested for both active and passive attenuation properties in a hemi-anechoic chamber using a head and torso simulator. Thirty-seven otology clinic patients then underwent standard audiometry and ANR audiometry, which was performed in a 30- and/or 40-dB sound field. Objective ANR headphone attenuation levels of up to 12 dB were achieved at frequencies below 2,000 Hz. In standard audiometric testing, 40 dB of narrow-band background noise decreased patient pure tone thresholds by 24 dB at 250 Hz. The use of ANR technology provided 12 dB of additional attenuation. This resulted in a significant improvement in test results despite the 40 dB of background noise (P = <0.001). In a 30-dB sound field, standard audiometric thresholds were shifted down by an average of 12 dB. The use of ANR technology completely attenuated this effect and resulted in a significant improvement in results (P = <0.01). These results were identical to those obtained in a quiet sound booth. Despite a 30-dB sound field, ANR audiometry can produce an audiogram identical to that obtained in a double-walled sound booth. ANR headphone audiometry improves the sensitivity of audiometric screening for mild low-frequency hearing loss. This technology may have important applications for screening in schools, industry, and community practices.

Enhancing the resolution of the subsurface by joint inversion of x- and z-component SkyTEM data

Numerical modelling shows that the resolution of the subsurface resistivity structures is significantly enhanced if transient electromagnetic (TEM) x- and z-component data are inverted jointly. The enhancement is most pronounced in the upper part of the model as the sensitivity kernel for the x-component is more ``condensed' compared to the corresponding kernel for the z-component. Best results are obtained if the ground is relatively conductive and therefore the method is best fitted for surveys where the average resistivities of the ground are below approximately 100 ohmm, e.g. mapping of saline layers and the layers above. In the field x-component data can be measured with only a few extra costs. However, whereas the method is simple in theory it is complicated in practice where a number of problems have to be addressed. Tilt of the x- and zcomponent receiver coils must be measured with an accuracy of better than 1. degree as even a small tilt adds a significantly amount of z-signal to the x-signal. This ?contamination? must be modelled in the forward response of the inversion algorithm and the tilt of the coils must be added as extra (constrained) inversion parameters. It is necessary to low-pass filter the x-component data in order to efficiently suppress the high frequency background noise. Finally the timing of the instrument must be better than 200 nanoseconds to be able to model the first time gate at 11 micro seconds. In the presentation we discuss the method, present a parameter sensitivity study and a field example using SkyTEM data collected at the Toolibin test line.