FFT Spectrum Research Articles

A High-Accuracy, High Anti-Noise, Unbiased Frequency Estimator Based on Three CZT Coefficients for Deep Space Exploration Mission.

Deep space exploration navigation requires high accuracy of the Doppler measurement, which is equivalent to a frequency estimation problem. Because of the fence effect and spectrum leakage, the frequency estimation performances, which is based on the FFT spectrum methods, are significantly affected by the signal frequency. In this paper, we propose a novel method that utilizes the mathematical relation of the three Chirp-Z Transform (CZT) coefficients around the peak spectral line. The realization, unbiased performance, and algorithm parameter setting rule of the proposed method are described and analyzed in detail. The Monte Carlo simulation results show that the proposed method has a better anti-noise and unbiased performance compared with some traditional estimator methods. Furthermore, the proposed method is utilized to process the raw data of MEX and Tianwen-1 satellites received by Chinese Deep Space Stations (CDSS). The results show that the Doppler estimation accuracy of MEX and Tianwen-1 are both about 3 millihertz (mHz) in 1-s integration, which is consistent with that of ESA/EVN/CDSN and a little better than that of the Chinese VLBI network (CVN). Generally, this proposed method can be effectively utilized to support Chinese future deep space navigation missions and radio science experiments.

DEVELOPMENT OF VIBRATIONS DUE TO CHANGING SPINDLE SPEEDS DURING MILLING

The article analyses the problem of measuring and examining the magnitudes of vibration amplitudes at the machining of materials by milling technology. By measuring the vibration parameter on the spindle head of a universal milling machine, the level of the vibration amplitudes magnitude during the milling process was acquired using a piezoelectric vibration sensor. The magnitudes of the vibration amplitudes were recorded during machining when the spindle speed varied between 1200 rpm and 1600 rpm. The measured values were evaluated in the form of FFT spectra, and the information required to design measures to avoid excess vibration amplitudes in such a case was obtained.

Online chatter detection considering beat effect based on Inception and LSTM neural networks

Chatter is an unstable and self-excited vibration that adversely affects part quality and tool life in various machining processes. To achieve high-performance machining, chatter identification has attracted considerable interest from many researchers in recent decades. Nevertheless, most existing chatter detection approaches fail to consider the presence of the beat effect, which is an interference pattern caused by slightly different chatter frequencies. The neglect of the beat effect would seriously degrade the effectiveness of these methods and even result in false alarms. In this paper, a novel deep neural network combining the Inception module, long short-term memory (LSTM) and residual networks (ILR-DNN) is proposed for online chatter detection considering the presence of the beat effect. The ILR-DNN automatically extracts insightful features from two branches. One branch is a two-layer LSTM network that can capture temporal characteristics of the chatter development process from the raw cutting force. In the other branch, a two-layer Inception network consisting of multiple convolutional kernel size filters extracts multiscale features from the FFT spectrum of the cutting force. Afterwards, the extracted features are concatenated and go through a residual network to alleviate the gradient disappearing during deep-layer network training. Finally, the fully-connected and softmax layers are employed to make a final classification. Machining tests are carried out, and cutting forces are collected to validate the feasibility and effectiveness of the proposed chatter detection method. Results show that the proposed ILR-DNN achieves much better performance than other methods in distinguishing machining states, i.e., stable machining, chatter with the beat effect, and chatter without the beat effect.

Calibration of an RF/Microwave Phase Noise Meter with a Photonic Delay Line

The main advantage of phase noise meters with photonic (fiber) delay lines is that they do not require high-performance, low-noise reference oscillators. On the other hand, some additional calibrations are required, which are the subject of this paper. First, the quadrature must be maintained on the mixer by precise adjustment of the phase and/or delay. Next, since the response of the mixer is proportional to the square of the input test signal, a precise amplitude calibration is required. Finally, the frequency response of the FFT spectrum analyzer and its corresponding anti-aliasing low-pass filter needs to be known precisely. In this paper, to the best of our knowledge, we present innovative solutions for all three calibrations. All three calibrations were built in and tested in our phase noise meter. The result is a simple and robust phase noise meter suitable for non-laboratory environments.

Remote Analysis of Respiratory Sounds in Patients With COVID-19: Development of Fast Fourier Transform-Based Computer-Assisted Diagnostic Methods.

BackgroundRespiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness.ObjectiveThe aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds.MethodsFast Fourier transform (FFT) was applied for computer analysis of respiratory sound recordings produced by hospital doctors near the mouths of 14 patients with COVID-19 (aged 18-80 years) and 17 healthy volunteers (aged 5-48 years). Recordings for 30 patients and 26 healthy persons (aged 11-67 years, 34, 60%, women), who agreed to be tested at home, were made by the individuals themselves using a mobile telephone; the records were passed for analysis using WhatsApp. For hospitalized patients, the illness was diagnosed using a set of medical methods; for outpatients, polymerase chain reaction (PCR) was used. The sampling rate of the recordings was from 44 to 96 kHz. Unlike usual computer-assisted diagnostic methods for illnesses based on respiratory sound analysis, we proposed to test the high-frequency part of the FFT spectrum (2000-6000 Hz).ResultsComparing the FFT spectra of the respiratory sounds of patients and volunteers, we developed 2 computer-assisted methods of COVID-19 diagnostics and determined numerical healthy-ill criteria. These criteria were independent of gender and age of the tested person.ConclusionsThe 2 proposed computer-assisted diagnostic methods, based on the analysis of the respiratory sound FFT spectra of patients and volunteers, allow one to automatically diagnose specific acoustic phenomena associated with COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive screening self-testing kits for COVID-19.

Dynamic modeling and analysis of the internal gear transmission with tooth crack subjected to the heavy torque

This work addresses the free and nonlinear vibrations of the internal gear transmission. A rigid-elastic coupled model is established using Hamilton's principle and the nonlinear in-extensional assumption, where the cracked time-varying mesh stiffnesses regarding torque-dependent and geometric nonlinearity caused by the heavy torque on the elastic ring gear are considered. Based on the coupled model, the natural frequencies and vibration mode shapes are given, and the distinctive modal properties associated with the torque are investigated by comparing with a rigid model. The differences of the nonlinear behaviors between the two models are presented through bifurcation diagrams, the largest Lyapunov exponent (LLE) diagrams, phase diagrams, Poincaré maps, time histories, and FFT spectra. The effects of parameters such as excitation frequency, torque, and crack depth on the dynamic responses are examined. The results show that the nonlinear behaviors are rich, and quasi-periodic motion replaces periodic-1 motion when the elasticity of the ring gear is considered. The dynamic responses indicate that the larger crack depth becomes, the more obvious the sidebands can be found in the frequency domain. As for lower excitation frequency, the main frequencies also include the mesh, elastic vibration, modulation, and natural frequencies.

Spray characterization in air-assist atomizers using flow-induced acoustic vibrations and multivariate analysis

This feasibility study investigated a new non-intrusive approach employing acoustic chemometrics. The method includes acoustic/vibration data recording obtained utilizing two clamp-on piezoelectric accelerometers and two electret condensers-type microphones mounted on an arc. Principal Component Analysis (PCA) classification models were based on the acoustic FFT spectra from four sensors. The non-dimensional number (X) values correspond to the different breakup regimes comprising a range of air and liquid (water) flow rates in this air-assisted atomizer (one-analyte system). PCA classification model discerns the clusters belonging to similar non-dimensional number (X) values with the maximum variance in the first principal component (PC1) direction for both sensors combined. This study also assesses the utility of the acoustic chemometrics approach for predicting the flow parameter, such as Sauter mean diameter (SMD) based on the Partial Least Squares-Regression (PLS-R). The PLS-R prediction models work best for the 550 mm location with a low root mean square error of prediction (RMSEP) value of 5.443 and a high Pearson correlation coefficient (R2) value of 0.856 when validated using 50% independent data (test set validation). The comparison between the two sensor types demonstrated superior prediction performance for accelerometers for all the prediction models.

High-Spatial-Resolution Strain and Vibration Dual-Parameter Sensor Based on Ultra-Short FBG

A method for simultaneous measurement of static strain and dynamic vibration with high spatial resolution based on millimeter sized ultra-short fiber Bragg grating (FBG) is proposed and experimented in this paper. Dual-parameter can be measured on the single unit of cascaded FBGs, which interrogate with optical coherence tomography method by a designed wavelength swept light source. In experiments, the sensing units were precisely located with mm degrees by inverse FFT of coherent signals and the phase difference calculation. And also the strain and vibration could be simultaneously measured in time and frequency domain: demodulating strain with low frequency component’s phase shift of coherent signals by extracting envelope and interpolation; demodulating vibration by finding peak positions of sidebands in FFT spectrum. Spatial resolution of positioning can reach 0.77 mm. Sensitivity of strain measurement reaches 0.811 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\times} 10^{-3} rad/\mu \varepsilon $</tex-math></inline-formula> under a wavelength sweep rate of 0.2 nm/ms, and forces of several milli newtons can be perceived. The measurement accuracy of kHz vibration frequency is over 98%. Moreover, by comparing simultaneous and respective measurement of dual-parameter, it can be seen that there is almost no crosstalk affectting the results. The results shows great application potential in the field of mechanical sensing, especially in bionic tactile sensing for its simultaneous dynamic and static measurement with accurate positioning performance.

Dynamic Modeling and Stability Analysis for a Spur Gear System Considering Gear Backlash and Bearing Clearance

In practice, gear backlash and bearing clearance usually exist together in a gear system. They may induce complicated dynamic responses and degrade transmission performance. Up to now, although each of them has been researched, little attention has been paid to the coupling dynamic characteristics of gear backlash and bearing clearance. In a limited number of relevant studies, since the linear collision models they adopted are difficult to realistically depict actual collision behaviors caused by bearing clearance, these studies cannot accurately reveal the coupling dynamic characteristics of gear backlash and bearing clearance. Furthermore, system stability of the gear system considering gear backlash and bearing clearance has not been thoroughly investigated. In view of this, this paper contributes to the research on dynamic modeling and stability analysis for the spur gear system considering gear backlash and bearing clearance. A nonlinear collision model with time-varying contact stiffness/damping is suggested for describing the bearing collision behaviors. Based on the geometrical relationship of dynamic center distance, dynamic working pressure angle, and dynamic backlash, the coupling motion model of gear backlash and bearing clearance is developed. On this basis, the dynamic model of the spur gear system considering gear backlash and bearing clearance is established and verified by numerical simulations, virtual prototyping simulations and experiments. Afterwards, to thoroughly explore the complicated dynamic characteristics of the gear system considering gear backlash and bearing clearance, several important parameters, i.e., rotational speed, gear backlash and bearing clearance, are chosen as bifurcation parameters to study their influences on system stability via bifurcation diagrams, time-domain waveforms, FFT spectra, Poincaré maps, and phase diagrams. Various complicated nonlinear behaviors, such as hopping, multiple periodic motion, quasi-periodic motion, and chaotic motion, are revealed. This study can provide useful reference for the multi-clearance coupling research of the gear system in complicated working environments.

Stall Warning Algorithm of Axial Compressor Based on SSA-DBN

&lt;p&gt;To solve the problem of stall warning for axial compressors, this paper proposes a stall warning algorithm based on the sparrow search algorithm, which optimizes the deep belief network. The deep belief network is trained by using deep learning to extract the FFT spectrum of compressor stall experiment data directly as the feature vector. To improve the accuracy of DBN classification, parameters of hidden layer nodes n and initial weights w of DBN were optimized by SSA algorithm, and stall warning algorithm model of SSA-DBN axial-flow compressor was established. The experimental results of the algorithms show that the stall data at each speed is at least 0.1～0.3s in advance for early warning. This method is 0.075~0.281s ahead of the various models from the past to the present, and noise is superimposed on the experimental data to verify the Robustness of the way, better surge warning margin performance, and engineering practicability. &lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Dynamic modeling and analysis of multistage planetary gear system considering tooth crack fault

Due to the influence of signal modulation and multi-stage coupling, the fault diagnosis of multi-stage planetary gear system is difficult. In this paper, a dynamic model of multi-stage planetary gear system containing sun gear crack is proposed from the perspective of nonlinear dynamics to study the failure mechanism and dynamic characteristics of tooth root crack. The mesh stiffness with root crack is calculated by using the modified energy method. By means of global bifurcation diagram, RMS curve, phase diagram, Poincare map, time series diagram and FFT spectrum, the dynamic responses of the system with and without fault are analyzed and compared. The results show that there are differences in the impact of crack failure on the dynamic characteristics at different rotational speeds. The crack disturbance will cause an abrupt change in the vibration amplitude of the system, which can excite the system into chaos from a quasi-periodic state. The system tends to be unstable due to crack failure, which is manifested by irregular expansion of the attractor, divergence of the phase trajectory, periodic pulses in the time series diagram, and sideband frequencies with the sun gear fault characteristic frequency as interval appearing around the meshing frequency. The chaotic motion range should be avoided during crack fault diagnosis.

Time domain and frequency domain of coated milling inserts using FFT spectrum

ABSTRACT Quality is determined by machines, materials, equipment, and lead times. The quality of aircraft materials such as aluminum and its alloys could greatly improve their applications. The difficulty of efficiently and reasonably machining certain materials limits their applicability. The purpose of this paper is to increase the quality of the vibration responses. Specifically, we examine the effects of the machining parameters on vibration (Time and Frequency domains). The end milling process is used to machine the AA6082T6 workpiece material. Speed (S), feed (F), depth of cut (DoC), and coated cutting inserts are the machining parameters. Tungsten carbide inserts (UNC), tungsten carbide inserts coated with Aluminum Chromium Nitride (AP3), and tungsten carbide inserts coated with Diamond-Like Carbon (DLC) were employed in this study. The minimum amplitude of 0.1173 g (m/s2) is seen at 710 rpm, 40 mm/min, and 0.5 mm of the DLC coated tool at a frequency of 930 Hz, according to the data. By comparing it to other cutting inserts, the DLC coated tool is given the smallest amplitude and minimum time domain. According to the findings, if the DLC coated insert is used in the machining process, the material’s surface finish will be much enhanced, and the material had good mechanical qualities.

Defect Diagnosis of Gear-Shaft Bearing System Based on the OWF-TSCNN Composed of Wavelet Time-Frequency Map and FFT Spectrum 1

In the defect diagnosis of the gear-shaft-bearing system with compound defects, the generated vibration signals are complicated. In addition, the information acquired by a single sensor is easily affected by uncertain factors, and low diagnostic accuracy is caused when traditional defect diagnosis methods are used, which cannot meet the high-precision diagnosis requirements. Therefore, a method is developed to identify the defect types and defect degrees of the gear-shaft-bearing system efficiently. In this method, the vibration signals are collected using multiple sensors, the dual-tree complex wavelet and the optimal weighting factor (OWF) methods are used for the data layer fusion, and the preprocessing is realized through wavelet transform and FFT. A learning model based on two-stream CNN composed of 1D-CNN and 2D-CNN is established, and the obtained wavelet time-frequency map and FFT spectrum are used as the input. Then, the trained features from the output of the connected layer are classified by the SVM. Compared with the OWF-1DCNN and OWF-2DCNN models, the time consumption of the OWF-TSCNN model is increased by 14.5%–26.6%, and the convergence speed of the network is decreased. However, its accuracy reaches 100% and 99.83% in the training set and test set, and the loss entropy and over-fitting rate are also greatly reduced. The feature extraction ability and generalization ability of the OWF-TSCNN model are increased, reaching 100% diagnosis accuracy on different defect types and defect degrees, which is more suitable for defect diagnosis of the gear-shaft-bearing system.

Effects of Al Content on Elastic Parameters of AlxGa1-xAs (0 ≤ x ≤ 1) Alloys

Elastic parameters of AlxGa1-xAs (0 ≤ x ≤ 1) alloys are numerically determined and analyzed on the basis of scanning acoustic microscopy technique. Thus, the dependence of Al concentrations, x, on all features of reflection coefficient and acoustic materials signatures (critical angles of reflected modes, spatial periods, peaks of FFT spectra and their corresponding wave velocities) has been considered, analyzed and discussed. It is found that as Al content increases several behaviors are obtained: (i) all critical angles of longitudinal, transverse and Rayleigh waves, decrease, (ii) all spatial periods increase and (ii) both Rayleigh and longitudinal wave velocities increase. Moreover, the variations of these parameters, P, were quantified and semi-empirical formulas were found to be of the form: P = c + ax + bx2; from these formulas, valuable information can be derived and may be useful for AlxGa1-xAs compositional characterization.

Enhancing Dynamic Response of Cantilevered Rectangular Prism Using a Splitter Plate as a Passive Turbulence Control in Water Tunnel

The effects of splitter plate as a passive turbulence control on the transverse vibration characteristics of a cantilevered rectangular prism with the different finite length (aspect ratio L/H) and depth ratios (side ratio D/H of 0.2 and 0.5) was investigated in a water tunnel. A splitter plate was installed behind the prism with a small gap and sufficient length to prevent vortex shedding intrusion. It enhances the response amplitude ascended linearly with respect to non-dimensional velocity. In the case of the prisms with critical points, interferences of amplitude signal spectra for the period of displacement vanished, yielding a uniform waveform on the response amplitude. Inserting a splitter plate improves the increment rate of the dynamic response of the test models. A brief numerical calculation was performed to find the quantities of flow features around a plain and rectangular prism with a detached splitter plate. The alteration of flow wake characteristics is found by diminishing unsymmetrical vortices shedding and reduce flow entrainment at the trailing edge. The essential findings of the prism with a detached splitter plate are the base pressure improvement, reducing drag force, and vanishing sharp peaks of wake FFT spectra.

FFT Spectrum Spread With Machine Learning (ML) Analysis of Triaxial Acceleration From Shirt Pocket and Torso for Sensing Coughs While Walking

FFT Spectrum Spread With Machine Learning (ML) Analysis of Triaxial Acceleration From Shirt Pocket and Torso for Sensing Coughs While Walking

A New Hybrid Algorithm to Image Lightning Channels Combining the Time Difference of Arrival Technique and Electromagnetic Time Reversal Technique

Very-high-frequency (VHF) electromagnetic signals have been well used to image lightning channels with high temporal and spatial resolution due to their capability to penetrate clouds. A lightning broadband VHF interferometer with three VHF antennas configured in a scalene-triangle shape has been installed in Lhasa since 2019, to detect the lightning VHF signals. Using the signals from the VHF interferometer, a new hybrid algorithm, called the TDOA-EMTR technique, combining the time difference of arrival (TDOA) and the electromagnetic time reversal (EMTR) technique is introduced to image the two-dimensional lightning channels. The TDOA technique is firstly applied to calculate the initial solutions for the whole lightning flash. According to the results by the TDOA method, the domain used for the EMTR technique is predetermined, and then the EMTR technique is operated to obtain the final positioning result. Unlike the original EMTR technique, the low-power frequency points for each time window are removed based on the FFT spectrum. Metrics used to filter noise events are adjusted. Detailed imaging results of a negative cloud-to-ground (CG) lightning flash and an intra-cloud (IC) lightning flash by the TDOA method and the TDOA-EMTR are presented. Compared with the original EMTR method, the positioning efficiency can be improved by more than a factor of 3 to 4, depending on the scope of the pre-determined domain. Results show that the new algorithm can obtain much weaker radiation sources and simultaneously occurring sources, compared with the TDOA method.

Re-Design of Machine Tool Joint Components Based on Polymer Fillings for High-Speed Performance.

In this paper, we report the results of an experimental study of a re-design approach using filling polymers and particulate composites with a polymer matrix, thus creating a macroscopic hybrid structure. The re-design is focused on the joint of a textile machine. It is a re-design of already existing machine parts of a joint in order to increase the damping of components, reduce the amplitudes of high-frequency vibrations and acoustic emission for high-speed operation of textile rotors, and to compare individual structural modifications of the rotor housing body and absorber of high-speed textile rotor in a spinning unit with respect to dynamic properties of that measured mechanical system. The experiments included a bump test, determination of logarithmic decrement, measurement of vibration acceleration, a wavelet analysis, and measurement of acoustic emission. When excited by high frequency signal amplitudes up to 5 g, the benefits of polymer filling were manifested by an approximately 50% reduction in amplitude vibrations, a 66% reduction in acoustic emission amplitude, and an 85% reduction of the maximum peak in the acoustic emission FFT spectrum. In the area above 10 g, the stiffness of the component dominated to reduce the magnitude of vibrations.

Time and frequency domain analysis of long-term heart rate variability in an experimental model of diet-induced metabolic syndrome

Abstract Background Metabolic syndrome (MetS) is defined as the set of at least three of the following conditions: central obesity, elevation of triglycerides, decreased in high-density lipoproteins, systemic hypertension and glucose intolerance. MetS is linked with a high prevalence of cardiovascular disease, including sudden cardiac death and atrial arrhythmias, which may be a consequence of changes related to the structure, function and autonomic control of the heart. One of the underlying mechanisms responsible could be the alteration of sinus node automaticity. Heart rate variability (HRV) analysis is a useful non-invasive tool for evaluating alterations in neural control of cardiac automaticity. Purpose To examine the changes in long-term HRV using time- and frequency- domain analyses in an experimental model of diet-induced MetS which develops all its components. Methods Male NZW rabbits were randomly assigned to control (n=10) or MetS group (n=10), fed with high-fat (10% coconut oil and 5% lard) and high sucrose (15% dissolved in water) diet during 28 weeks. At week 28, 24 hour ECG recording was performed (eMotion Faros 180, Mega Electronics®, 1 kHz). We analyzed 60 minutes of RR time series, comparing day (from 8:00 to 19:59 h) and night (from 20:00 to 7:59 h), and quantified the standard parameters of time and frequency domains: 1) Time domain: RR, SDNN, triangular index (Ti), RMSSD and TINN; 2) Frequency domain: very low (VLF), low (LF), high frequency (HF), and LF/HF index. Multivariate analysis of variance (MANOVA, factorial model) was used for statistical analysis (p&amp;lt;0.05). Results Time domain analysis showed a decrease in RR interval (p&amp;lt;0.001) and geometrical Ti (p=0.036) in MetS animals (Figure, A-B), indicative of an increased heart rate. The rest of parameters in the time domain (SDNN, RMSSD, TINN) were not modified. Further, in the frequency domain at FFT spectrum, we did find a significant decrease in the LF band (p=0.032) in MetS animals (Figure, C). The rest of the frequency domain parameters (VLF, HF and LF/HF index) remained unchanged. Conclusion MetS decreased RR interval duration and triangular index, suggesting an increased sympathetic activity during day and night. Those changes were reflected in LF modifications, and might be attributable to a deficiency in sympathetic-parasympathetic control, which requires adjustments to maintain normal autonomic balance. Collectively, these results could give insight into the autonomic mechanisms that underlie increased atrial arrhythmia susceptibility in MetS. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Generalitat Valenciana, University of Valencia

Acoustic features of Hadza clicks

Hadza (Khoesan) has several clicks in its sound inventory [1,2]. There are 4 types of clicks in the language: bilabial, dental, alveolar and lateral [⊙, |, !, ‖] that can be accompanied, by aspirated, glottal and nasal features [⊙∼ , |ʔ, |h, ŋ|, ŋ|ʔ, !ʔ, !h, ŋ!, ŋ!ʔ, ‖, ‖h, ŋ‖h, ŋ‖ʔ]. Our study was made with 9 native speakers (4 women and 5 men) using various instrumental techniques (Acoustic, aerodynamic, EGG and Video). Clicks have two components: an attack and an extinction transient. Bilabial clicks have a noisy release, sometimes whisteled. Aspiration is short for dentals and alveolars, long for laterals. Glottals have a long lag after the burst release. The 4 types of clicks can be produced with the nasal feature. Acoustically, clicks are described with 2 features [grave versus acute] and [abrupt versus noisy] [3]. The [grave] feature has a peak in the FFT spectrum around 1200Hz and the [acute] around 3000 Hz. For some clicks, the cavity posterior to the constriction is excited. Short resonances occur between 1 and 2 kHz following the posterior release, they result from the lowering of the tongue dorsum and from the reduction in the volume of the pharyngeal cavity. [1] K. Miller, Hadza Grammar Notes (Ms Riezlern, 2008). [2] B. Sands, “Phonetics and phonology: Hadza,” in The Khoesan languages, edited by R. Vössen (Routledge, London, 2013). [3] A. Traill, s“The perception of clicks in !xoo,” J. African Lang. Linguist. 15, 161–174 (1994).