Search results for: vibration signals

Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Ahmed Saeed Mohamed, Sadok Sassi, Mohammad Roshun Paurobally

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Gears are important machine components that are widely used to transmit power and change speed in many rotating machines. Any breakdown of these vital components may cause severe disturbance to production and incur heavy financial losses. One of the most common causes of gear failure is the tooth fatigue crack. Early detection of teeth cracks is still a challenging task for engineers and maintenance personnel. So far, to analyze the vibration behavior of gears, different approaches have been tried based on theoretical developments, numerical simulations, or experimental investigations. The objective of this study was to develop a numerical model that could be used to simulate the effect of teeth cracks on the resulting vibrations and hence to permit early fault detection for gear transmission systems. Unlike the majority of published papers, where only one single crack has been considered, this work is more realistic, since it incorporates the possibility of multiple simultaneous cracks with different lengths. As cracks significantly alter the gear mesh stiffness, we performed a finite element analysis using SolidWorks software to determine the stiffness variation with respect to the angular position for different combinations of crack lengths. A simplified six degrees of freedom non-linear lumped parameter model of a one-stage gear system is proposed to study the vibration of a pair of spur gears, with and without tooth cracks. The model takes several physical properties into account, including variable gear mesh stiffness and the effect of friction, but ignores the lubrication effect. The vibration simulation results of the gearbox were obtained via Matlab and Simulink. The results were found to be consistent with the results from previously published works. The effect of one crack with different levels was studied and very similar changes in the total mesh stiffness and the vibration response, both were observed and compared to what has been found in previous studies. The effect of the crack length on various statistical time domain parameters was considered and the results show that these parameters were not equally sensitive to the crack percentage. Multiple cracks are introduced at different locations and the vibration response and the statistical parameters were obtained.

Keywords: dynamic simulation, gear mesh stiffness, simultaneous tooth cracks, spur gear, vibration-based fault detection

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Authors: Ziraguen O. Williams, Shield B. Lin, Fouad N. Matari, Leslie J. Quiocho

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Simulation for seated row exercise was a continued task to assist NASA in analyzing a one-dimensional vibration isolation and stabilization system for astronaut’s exercise platform. Feedback delay and signal noise were added to the model as previously done in simulation for squat exercise. Simulation runs for this study were conducted in two software simulation tools, Trick and MBDyn, software simulation environments developed at the NASA Johnson Space Center. The exciter force in the simulation was calculated from the motion capture of an exerciser during a seated row exercise. The simulation runs include passive control, active control using a Proportional, Integral, Derivative (PID) controller, and active control using a Piecewise Linear Integral Derivative (PWLID) controller. Output parameters include displacements of the exercise platform, the exerciser, and the counterweight; transmitted force to the wall of spacecraft; and actuator force to the platform. The simulation results showed excellent force reduction in the actively controlled system compared to the passive controlled system, which showed less force reduction.

Keywords: control, counterweight, isolation, vibration.

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Authors: Dhawal Ladani

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Shell and tube type heat exchangers are predominantly used in heat exchange between two fluids and other applications. This paper projects the optimal design of the pipe used in the heat exchanger in such a way to minimize the vibration occurring in the pipe. Paper also consists of the comparison of the different design of the pipe to get the maximize the heat transfer rate by converting laminar flow into the turbulent flow. By the updated design the vibration in the pipe due to the flow is also decreased. Computational Fluid Dynamics and Thermal Heat Transfer analysis are done to justifying the result. Currently, the straight pipe is used in the shell and tube type of heat exchanger where as per the paper the pipe consists of the curvature along with the pipe. Hence, the heat transfer area is also increased and result in the increasing in heat transfer rate. Curvature type design is useful to create turbulence and minimizing the vibration, also. The result will give the output comparison of the effect of laminar flow and the turbulent flow in the heat exchange mechanism, as well as, inverse effect of the boundary layer in heat exchanger is also justified.

Keywords: heat exchanger, heat transfer rate, laminar and turbulent effect, shell and tube

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Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara

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Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.

Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement

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Authors: Houari Boumediene University of Science, Technology.

Abstract:

"Various methods are typically used in the dynamic analysis of transversely vibrating beams. To achieve this, numerical methods are used to solve the general eigenvalue problem. The equations of equilibrium, which describe the motion, are derived from a fourth-order differential equation. Our study is based on the finite element method, and the results of the investigation are the vibration frequencies obtained using the Jacobi method. Two types of elementary mass matrices are considered: one representing a uniform distribution of mass along the element and the other consisting of concentrated masses located at fixed points whose number increases progressively with equal distances at each evaluation stage. The beams studied have different boundary constraints, representing several classical situations. Comparisons are made for beams where the distributed mass is replaced by n concentrated masses. As expected, the first calculation stage involves determining the lowest number of beam parts that gives a frequency comparable to that obtained from the Rayleigh formula. The obtained values are then compared to theoretical results based on the assumptions of the Bernoulli-Euler theory. These steps are repeated for the second type of mass representation in the same manner."

Keywords: finite element method, bernouilli eulertheory, structural analysis, vibration analysis, rayleigh quotient

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Authors: Somya R. Patro, Arnab Banerjee, G. V. Ramana

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A flexural beam carrying elastically mounted concentrated masses, such as engines, motors, oscillators, or vibration absorbers, is often encountered in mechanical, civil, and aeronautical engineering domains. To prevent resonance conditions, the designers must predict the natural frequencies of such a constrained beam system. This paper investigates experimental and analytical studies on vibration suppression in a cantilever beam with a tip mass with the help of spring-mass to achieve local resonance conditions. The system consists of a 3D printed polylactic acid (PLA) beam screwed at the base plate of the shaker system. The top of the free end is connected by an accelerometer which also acts as a tip mass. A spring and a mass are attached at the bottom to replicate the mechanism of the spring-mass resonator. The Fast Fourier Transform (FFT) algorithm converts time acceleration plots into frequency amplitude plots from which transmittance is calculated as a function of the excitation frequency. The mathematical formulation is based on the transfer matrix method, and the governing differential equations are based on Euler Bernoulli's beam theory. The experimental results are successfully validated with the analytical results, providing us essential confidence in our proposed methodology. The beam spring-mass system is then converted to an equivalent two-degree of freedom system, from which frequency response function is obtained. The H2 optimization technique is also used to obtain the closed-form expression of optimum spring stiffness, which shows the influence of spring stiffness on the system's natural frequency and vibration response.

Keywords: euler bernoulli beam theory, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

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Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: edge effect, scale optimization, small crack locating, spatial wavelet

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Authors: Prabhakar Sathujoda

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Vibration analysis of a misaligned rotor coupling bearing system has been carried out while decelerating through its critical speed. The finite element method (FEM) is used to model the rotor system and simulate flexural vibrations. A flexible coupling with a frictionless joint is considered in the present work. The continuous wavelet transform is used to extract the misalignment features from the simulated time response. Subcritical speeds at one-half, one-third, and one-fourth the critical speed have appeared in the wavelet transformed vibration response of a misaligned rotor coupling bearing system. These features are also verified through a parametric study.

Keywords: Continuous Wavelet Transform, Flexible Coupling, Rotor System, Sub Critical Speed

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Authors: Azza M. Atya, Mahmoud M. Nasser

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Background/ /Significance: Peripheral neuropathy is one of the long term serious complications of diabetes, which may attribute to postural instability and alteration of planter pressure. Whole body vibration (WBV) is a somatosensory stimulation type of exercise that has been emerged in sport training and rehabilitation of neuromuscular disorders. Purpose: The aim of this study was to investigate the effect of whole Body Vibration on antroposterior (AP), mediolateral (ML) posture stability and planter foot pressure in patients with diabetic neuropathy. Subjects: forty diabetic patients with moderate peripheral neuropathy aged from 35 to 50 years, were randomly assigned to WBV group (n=20) and control group (n=20). Methods and Materials: the WBV intervention consisted of three session weekly for 8 weeks (frequency 20 Hz, peak-to peak displacement 4mm, acceleration 3.5 g). Biodex balance system was used for postural stability assessment and the foot scan plate was used to measure the mean peak pressure under the first and lesser metatarsals. The main Outcome measures were antroposterior stability index (APSI), mediolateral stability index (MLSI), overall stability index (OSI),and mean peak foot pressure. Analyses: Statistical analysis was performed using the SPSS software package (SPSS for Windows Release 18.0). T-test was used to compare between the pre- and post-treatment values between and within groups. Results: For the 40 study participants (18male and 22 females) there were no between-group differences at baseline. At the end of 8 weeks, Subjects in WBV group experienced significant increase in postural stability with a reduction of mean peak of planter foot pressure (P<0.05) compared with the control group. Conclusion: The result suggests that WBV is an effective therapeutic modality for increasing postural stability and reducing planter pressure in patients with diabetic neuropathy.

Keywords: whole body vibration, diabetic neuropathy, posture stability, foot pressure

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Authors: Muchun Yu, Xue Gao, Qian Chen

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As a novel passive vibration isolation technology, molecular spring isolator (MSI) is investigated in this paper. An MSI consists of water and hydrophobic zeolites as working medium. Under periodic excitation, water molecules intrude into hydrophobic pores of zeolites when the pressure rises and water molecules extrude from hydrophobic pores when pressure drops. At the same time, energy is stored, released and dissipated. An MSI of piston-cylinder structure was designed in this work. Experiments were conducted to investigate the stiffness properties of MSI. The results show that MSI exhibits high-static-low dynamic (HSLD) stiffness. Furthermore, factors such as the quantity of zeolites, temperature, and ions in water are proved to have an influence on the stiffness properties of MSI.

Keywords: hydrophobic zeolites, molecular spring, stiffness, vibration isolation

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Authors: Deborah Zelinsky

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The retina filters millions of incoming signals into a smaller amount of exiting optic nerve fibers that travel to different portions of the brain. Most of the signals are for eyesight (called "image-forming" signals). However, there are other faster signals that travel "elsewhere" and are not directly involved with eyesight (called "non-image-forming" signals). This article centers on the neurons of the optic nerve connecting to parts of the limbic system. Eye care providers are currently looking at parvocellular and magnocellular processing pathways without realizing that those are part of an enormous "galaxy" of all the body systems. Lenses are modifying both non-image and image-forming pathways, taking A.M. Skeffington's seminal work one step further. Almost 100 years ago, he described the Where am I (orientation), Where is It (localization), and What is It (identification) pathways. Now, among others, there is a How am I (animation) and a Who am I (inclination, motivation, imagination) pathway. Classic eye testing considers pupils and often assesses posture and motion awareness, but classical prescriptions often overlook limbic involvement in visual processing. The limbic system is composed of the hippocampus, amygdala, hypothalamus, and anterior nuclei of the thalamus. The optic nerve's limbic connections arise from the intrinsically photosensitive retinal ganglion cells (ipRGC) through the "retinohypothalamic tract" (RHT). There are two main hypothalamic nuclei with direct photic inputs. These are the suprachiasmatic nucleus and the paraventricular nucleus. Other hypothalamic nuclei connected with retinal function, including mood regulation, appetite, and glucose regulation, are the supraoptic nucleus and the arcuate nucleus. The retino-hypothalamic tract is often overlooked when we prescribe eyeglasses. Each person is different, but the lenses we choose are influencing this fast processing, which affects each patient's aiming and focusing abilities. These signals arise from the ipRGC cells that were only discovered 20+ years ago and do not address the campana retinal interneurons that were only discovered 2 years ago. As eyecare providers, we are unknowingly altering such factors as lymph flow, glucose metabolism, appetite, and sleep cycles in our patients. It is important to know what we are prescribing as the visual processing evaluations expand past the 20/20 central eyesight.

Keywords: neuromodulation, retinal processing, retinohypothalamic tract, limbic system, visual processing

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Authors: Nneka Osuchukwu, Leonid Shpanin

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The concept of converting the kinetic energy of quadcopter propellers into electrical energy is considered in this contribution following the feasibility study of the propeller vibrations, theoretical energy conversion, and simulation techniques. Analysis of the propeller vibration performance is presented via graphical representation of calculated and simulated parameters, in order to demonstrate the possibility of recovering the harvested energy from the propeller vibrations of the quadcopter while the quadcopter is in operation. Consideration of using piezoelectric materials in such concept, converting the mechanical energy of the propeller into the electrical energy, is given. Photographic evidence of the propeller in operation is presented and discussed together with experimental results to validate the theoretical concept.

Keywords: energy harvesting, piezoelectric material, propeller vibration, unmanned aerial vehicle

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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Authors: Mor Diama L. O., Matthieu Davy, Laurent Ferro-Famil

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In this article, inverse synthetic aperture radar (ISAR) is combined with compressive imaging techniques in order to perform 3D interferometric imaging. Interferometric ISAR (InISAR) imaging relies on a two-dimensional antenna array providing diversities in the elevation and azimuth directions. However, the signals measured over several antennas must be acquired by coherent receivers resulting in costly and complex hardware. This paper proposes to use a chaotic cavity as a compressive device to encode the signals arising from several antennas into a single output port. These signals are then reconstructed by solving an inverse problem. Our approach is demonstrated experimentally with a 3-elements L-shape array connected to a metallic compressive enclosure. The interferometric phases estimated from a unique broadband signal are used to jointly estimate the target’s effective rotation rate and the height of the dominant scattering centers of our target. Our experimental results show that the use of the compressive device does not adversely affect the performance of our imaging process. This study opens new perspectives to reduce the hardware complexity of high-resolution ISAR systems.

Keywords: interferometric imaging, inverse synthetic aperture radar, compressive device, computational imaging

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Authors: Saeed Kamarian

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In this paper, free vibrations of Functionally Graded Sandwich (FGS) beams reinforced by randomly oriented Single-Walled Carbon Nanotubes (SWCNTs) are investigated. The Eshelby–Mori–Tanaka approach based on an equivalent fiber is used to investigate the material properties of the structure. The natural frequencies of the FGS nanocomposite beam are analyzed based on various Higher-order Shear Deformation Beam Theories (HSDBTs) and using an analytical method. The verification study represents the simplicity and accuracy of the method for free vibration analysis of nanocomposite beams. The effects of carbon nanotube volume fraction profiles in the face layers, length to span ratio and thicknesses of face layers on the natural frequency of structure are studied for the different HSDBTs. Results show that by utilizing the FGS type of structures, free vibration characteristics of structures can be improved. A comparison is also provided to show the difference between natural frequency responses of the FGS nanocomposite beam reinforced by aligned and randomly oriented SWCNT.

Keywords: sandwich beam, nanocomposite beam, functionally graded materials, higher-order beam theories, Mori-Tanaka approach

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Authors: Rohit Shrivastava, Stefan Luding

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A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Chafik Barnoussi, Mourad Talbi, Adnane Cherif

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In this paper we propose a new speech compression system based on the application of the Bionic Wavelet Transform (BWT) combined with the psychoacoustic model. This compression system is a modified version of the compression system using a MDCT (Modified Discrete Cosine Transform) filter banks of 32 filters each and the psychoacoustic model. This modification consists in replacing the banks of the MDCT filter banks by the bionic wavelet coefficients which are obtained from the application of the BWT to the speech signal to be compressed. These two methods are evaluated and compared with each other by computing bits before and bits after compression. They are tested on different speech signals and the obtained simulation results show that the proposed technique outperforms the second technique and this in term of compressed file size. In term of SNR, PSNR and NRMSE, the outputs speech signals of the proposed compression system are with acceptable quality. In term of PESQ and speech signal intelligibility, the proposed speech compression technique permits to obtain reconstructed speech signals with good quality.

Keywords: speech compression, bionic wavelet transform, filterbanks, psychoacoustic model

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Authors: Mary S. Ruppert-Stroescu, Minh Pham, Bruce Benjamin

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Sleep apnea is a condition where a person stops breathing and can lead to cardiovascular disease, hypertension, and stroke. In the United States, approximately forty percent of overnight sleep apnea detection tests are cancelled. The purpose of this study was to develop a textile-based sensing system that acquires biometric signals relevant to cardiovascular health, to transmit them wirelessly to a computer, and to quantitatively assess the signals for sleep apnea detection. Patient interviews, literature review and market analysis defined a need for a device that ubiquitously integrated into the patient’s lifestyle. A multi-disciplinary research team of biomedical scientists, apparel designers, and computer engineers collaborated to design a textile-based sensing system that gathers EKG, Sp02, and respiration, then wirelessly transmits the signals to a computer in real time. The electronic components were assembled from existing hardware, the Health Kit which came pre-set with EKG and Sp02 sensors. The respiration belt was purchased separately and its electronics were built and integrated into the Health Kit mother board. Analog ECG signals were amplified and transmitted to the Arduino™ board where the signal was converted from analog into digital. By using textile electrodes, ECG lead-II was collected, and it reflected the electrical activity of the heart. Signals were collected when the subject was in sitting position and at sampling rate of 250 Hz. Because sleep apnea most often occurs in people with obese body types, prototypes were developed for a man’s size medium, XL, and XXL. To test user acceptance and comfort, wear tests were performed on 12 subjects. Results of the wear tests indicate that the knit fabric and t-shirt-like design were acceptable from both lifestyle and comfort perspectives. The airflow signal and respiration signal sensors return good signals regardless of movement intensity. Future study includes reconfiguring the hardware to a smaller size, developing the same type of garment for the female body, and further enhancing the signal quality.

Keywords: sleep apnea, sensors, electronic textiles, wearables

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Authors: Panupat Chaiworn, Soraya lama

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We study the motion of particles in cylinders which are subjected to a sinusoidal vertical vibration. We measure the rising time of a large intruder from the bottom of the container to free surface of the bed particles and find that the rising time as a function of intruder density increases to a maximum and then decreases monotonically. The result is qualitatively accord to the previous findings in experiments using relative humidity of the bed particles and found speed convection of the bed particles containers it moving slowly, and the rising time of the intruder where a minimal instead of maximal rising time in the small density region was found. Our experimental results suggest that the topology of the container plays an important role in the Brazil nut effect.

Keywords: granular particles, Brazil nut effect, cylinder container, vertical vibration, convection

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Matza Gusto Andika, Malinda Sabrina, Syarie Fatunnisa

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Aerodynamic and aeroelastics studies on the hanger bridge profile are important to analyze the aerodynamic phenomenon and Aeroelastics stability of hanger. Wind tunnel tests were conducted on a model of H-beam profile from hanger bridge. The purpose of this study is to investigate steady aerodynamic characteristics such as lift coefficient (Cl), drag coefficient (Cd), and moment coefficient (Cm) under the different angle of attack for preliminary prediction of aeroelastics stability problems. After investigation the steady aerodynamics characteristics from the model, dynamic testing is also conducted in wind tunnel to know the aeroelastics phenomenon which occurs at the H-beam hanger bridge profile. The studies show that the torsional vortex induced vibration occur when the wind speed is 7.32 m/s until 9.19 m/s with maximum amplitude occur when the wind speed is 8.41 m/s. The result of wind tunnel testing is matching to hanger vibration where occur in the field, so wind tunnel studies has successful to model the problem. In order that the H-beam profile is not good enough for the hanger bridge and need to be modified to minimize the Aeroelastics problem. The modification can be done with structure dynamics modification or aerodynamics modification.

Keywords: aerodynamics, aeroelastic, hanger bridge, h-beam profile, vortex induced vibration, wind tunnel

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Bochen Jia, Francesco Zhu

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People are constantly surprised at how real and immersive virtual reality (VR) is, even though the technology is still rudimentary, and we are only scratching the surface of its possibilities. Therefore, this literature review built a body of knowledge of existing technology that can be used to improve immersiveness in VR. For this paper, "Sense of Presence (SoP)" was chosen as the terminology to describe immersiveness in VR. Eight studies that tested VR technologies were identified. Many other studies were included to back up the incentives behind these technologies. VR technologies include vibration, airflow, thermal components, EMS, and quadcopters. Study results from selected papers were analyzed, compared, and generally positive. Seven studies had positive results, and only one had negative results. Vibration is the most effective option to improve SoP.

Keywords: virtual reality, sense of presence, self-awareness, literature review

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Authors: Ya-Chi Yu, Pei-Syuan Ruan, Shao-Wen Chen, Yu-Hsien Chang, Jin-Der Lee, Jong-Rong Wang, Chunkuan Shih

Abstract:

This study analyzed the transient signals of central region void fraction of air-water two-phase flow in a 3x3 rod bundle. Experimental tests were carried out utilizing a vertical rod bundle test section along with a set of air-water supply/flow control system, and the transient signals of the central region void fraction were collected through the electrical conductivity sensors as well as visualized via high speed photography. By converting the electric signals, transient void fraction can be obtained through the voltage ratios. With a fixed superficial water velocity (J_f=0.094 m/s), two different superficial air velocities (J_g=0.094 m/s and 0.236 m/s) were tested and presented, which were corresponding to the flow conditions of bubbly flows and cap/slug flows, respectively. The time averaged central region void fraction was obtained as 0.109-0.122 with 0.028 standard deviation for the selected bubbly flow and 0.188-0.221with 0.101 standard deviation for the selected cap/slug flow, respectively. Through Fast Fourier Transform (FFT) analysis, no clear frequency peak was found in bubbly flow, while two dominant frequencies were identified around 1.6 Hz and 2.5 Hz in the present cap/slug flow.

Keywords: central region, rod bundles, transient void fraction, two-phase flow

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Authors: Indika Fernando, Jiangang Fei, Roger Stanley, Hossein Enshaei

Abstract:

Delicate produce such as fresh fruits are increasingly susceptible to physiological damage during the essential post-harvest operations such as transport and handling. Vibration and shock during the distribution are identified factors for produce damage within post-harvest supply chains. Mechanical damages caused during transit may significantly diminish the quality of fresh produce which may also result in a substantial wastage. Bananas are one of the staple fruit crops and the most sold supermarket produce in Australia. It is also the largest horticultural industry in the state of Queensland where 95% of the total production of bananas are cultivated. This results in significantly lengthy interstate supply chains where fruits are exposed to prolonged vibration and shocks. This paper is focused on determining the shock and vibration levels experienced by packaged bananas during transit from the farm gate to the retail market. Tri-axis acceleration data were captured by custom made accelerometer based data loggers which were set to a predetermined sampling rate of 400 Hz. The devices recorded data continuously for 96 Hours in the interstate journey of nearly 3000 Km from the growing fields in far north Queensland to the central distribution centre in Melbourne in Victoria. After the bananas were ripened at the ripening facility in Melbourne, the data loggers were used to capture the transport and handling conditions from the central distribution centre to three retail outlets within the outskirts of Melbourne. The quality of bananas were assessed before and after transport at each location along the supply chain. Time series vibration and shock data were used to determine the frequency and the severity of the transient shocks experienced by the packages. Frequency spectrogram was generated to determine the dominant frequencies within each segment of the post-harvest supply chain. Root Mean Square (RMS) acceleration levels were calculated to characterise the vibration intensity during transport. Data were further analysed by Fast Fourier Transform (FFT) and the Power Spectral Density (PSD) profiles were generated to determine the critical frequency ranges. It revealed the frequency range in which the escalated energy levels were transferred to the packages. It was found that the vertical vibration was the highest and the acceleration levels mostly oscillated between ± 1g during transport. Several shock responses were recorded exceeding this range which were mostly attributed to package handling. These detrimental high impact shocks may eventually lead to mechanical damages in bananas such as impact bruising, compression bruising and neck injuries which affect their freshness and visual quality. It was revealed that the frequency range between 0-5 Hz and 15-20 Hz exert an escalated level of vibration energy to the packaged bananas which may result in abrasion damages such as scuffing, fruit rub and blackened rub. Further research is indicated specially in the identified critical frequency ranges to minimise exposure of fruits to the harmful effects of vibration. Improving the handling conditions and also further study on package failure mechanisms when exposed to transient shock excitation will be crucial to improve the visual quality of bananas within the post-harvest supply chain in Australia.

Keywords: bananas, handling, post-harvest, supply chain, shocks, transport, vibration

Procedia PDF Downloads 157

Authors: Chia-Ju Peng, Shih-Jui Chen

Abstract:

This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

Procedia PDF Downloads 375

Authors: Azad Mohammed Ali Saber, Lanja Saeed Omer

Abstract:

The present study deals with numerical method (FE) and experimental investigations on the vibration behavior of carbon fiber-polyester laminated plates. Finite element simulation is done using APDL (Ansys Parametric Design Language) macro codes software version 19. Solid185 layered structural element, including eight nodes, is adopted in this analysis. The experimental work is carried out using (Hand Layup method) to fabricate different layers and orientation angles of composite laminate plates. Symmetric samples include four layers (00/900)s and six layers (00/900/00)s, (00/00/900)s. Antisymmetric samples include one layer (00), (450), two layers (00/900), (-450/450), three layers (00/900/00), four layers (00/900)2, (-450/450)2, five layers (00/900)2.5, and six layers (00/900)3, (-450/450)3. An experimental investigation is carried out using a modal analysis technique with a Fast Fourier Transform Analyzer (FFT), Pulse platform, impact hammer, and accelerometer to obtain the frequency response functions. The influences of different parameters such as the number of layers, aspect ratio, modulus ratio, ply orientation, and different boundary conditions on the dynamic behavior of the CFRPs are studied, where the 1st, 2nd, and 3rd natural frequencies are observed to be the minimum for cantilever boundary condition (CFFF) and the maximum for full clamped boundary condition (CCCC). Experimental results show that the natural frequencies of laminated plates are significantly reliant on the type of boundary conditions due to the restraint effect at the edges. Good agreement is achieved among the finite element and experimental results. All results indicate that any increase in aspect ratio causes a decrease in the natural frequency of the CFRPs plate, while any increase in the modulus ratio or number of layers causes an increase in the fundamental natural frequency of vibration.

Keywords: vibration, composite materials, finite element, APDL ANSYS

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

Abstract:

The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

Procedia PDF Downloads 92