Search results for: signal blocking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1769

Search results for: signal blocking

1619 A Time Delay Neural Network for Prediction of Human Behavior

Authors: A. Hakimiyan, H. Namazi

Abstract:

Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

Procedia PDF Downloads 641
1618 A Communication Signal Recognition Algorithm Based on Holder Coefficient Characteristics

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

Procedia PDF Downloads 123
1617 Embedded System of Signal Processing on FPGA: Underwater Application Architecture

Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

Abstract:

The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

Procedia PDF Downloads 54
1616 Effect of Signal Acquisition Procedure on Imagined Speech Classification Accuracy

Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

Abstract:

Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

Procedia PDF Downloads 128
1615 Clinical Implication of Hyper-Intense Signal Thyroid Incidentaloma on Time of Flight Magnetic Resonance Angiography

Authors: Inseon Ryoo, Soo Chin Kim, Hyena Jung, Sangil Suh

Abstract:

Objectives: The purpose of this study is to evaluate the clinical significance of hyper-intense signal thyroid incidentalomas on the time of flight magnetic resonance angiography (TOF-MRA) using correlation study with ultrasound (US). Methods: We retrospectively reviewed 3,505 non-contrast TOF-MRA performed at an institution between September 2014 and May 2017. Two radiologists correlated the thyroid incidentalomas detected on TOF-MRA with US features which was obtained within three months interval between MRA and US examinations in consensus method. Results: The prevalence of hyper-intense signal thyroid nodules incidentally detected on TOF-MRA was 1.2% (43/3505). Among them, 35 people (81.4%) underwent US examinations, and total 45 hyper-intense signal thyroid nodules were detected on US exams. Of these 45 nodules, 35 nodules (72.9%) were categorized as benign (K-TIRADS category 2) on US exams. Fine needle aspiration was performed on 9 nodules according to the indications recommended by Korean Society of Thyroid Radiology. All except one high-suspicious thyroid nodule were confirmed as benign (Bethesda 2) on cytologic exams. One high-suspicious nodule on US showed a non-diagnostic result (Bethesda 1) on cytologic exam. However, this nodule collapsed after aspiration of thick colloid material. Conclusions: Our study showed that the most hyper-intense signal thyroid nodules detected on TOF-MRA were benign. Therefore, if a hyper-intense signal incidentaloma is found on TOF-MRA, further evaluation, especially invasive biopsy of the nodules could be suspended unless the patient had other symptoms or clinical factors suggesting the need for further evaluation.

Keywords: incidentaloma, thyroid nodule, TOF MR angiography, ultrasound

Procedia PDF Downloads 146
1614 Modeling of Digital and Settlement Consolidation of Soil under Oedomete

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 308
1613 Assessing the Effect of Grid Connection of Large-Scale Wind Farms on Power System Small-Signal Angular Stability

Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

Abstract:

Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

Procedia PDF Downloads 461
1612 THz Phase Extraction Algorithms for a THz Modulating Interferometric Doppler Radar

Authors: Shaolin Allen Liao, Hual-Te Chien

Abstract:

Various THz phase extraction algorithms have been developed for a novel THz Modulating Interferometric Doppler Radar (THz-MIDR) developed recently by the author. The THz-MIDR differs from the well-known FTIR technique in that it introduces a continuously modulating reference branch, compared to the time-consuming discrete FTIR stepping reference branch. Such change allows real-time tracking of a moving object and capturing of its Doppler signature. The working principle of the THz-MIDR is similar to the FTIR technique: the incoming THz emission from the scene is split by a beam splitter/combiner; one of the beams is continuously modulated by a vibrating mirror or phase modulator and the other split beam is reflected by a reflection mirror; finally both the modulated reference beam and reflected beam are combined by the same beam splitter/combiner and detected by a THz intensity detector (for example, a pyroelectric detector). In order to extract THz phase from the single intensity measurement signal, we have derived rigorous mathematical formulas for 3 Frequency Banded (FB) signals: 1) DC Low-Frequency Banded (LFB) signal; 2) Fundamental Frequency Banded (FFB) signal; and 3) Harmonic Frequency Banded (HFB) signal. The THz phase extraction algorithms are then developed based combinations of 2 or all of these 3 FB signals with efficient algorithms such as Levenberg-Marquardt nonlinear fitting algorithm. Numerical simulation has also been performed in Matlab with simulated THz-MIDR interferometric signal of various Signal to Noise Ratio (SNR) to verify the algorithms.

Keywords: algorithm, modulation, THz phase, THz interferometry doppler radar

Procedia PDF Downloads 308
1611 Compressed Sensing of Fetal Electrocardiogram Signals Based on Joint Block Multi-Orthogonal Least Squares Algorithm

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

Procedia PDF Downloads 104
1610 Magnetic Carriers of Organic Selenium (IV) Compounds: Physicochemical Properties and Possible Applications in Anticancer Therapy

Authors: E. Mosiniewicz-Szablewska, P. Suchocki, P. C. Morais

Abstract:

Despite the significant progress in cancer treatment, there is a need to search for new therapeutic methods in order to minimize side effects. Chemotherapy, the main current method of treating cancer, is non-selective and has a number of limitations. Toxicity to healthy cells is undoubtedly the biggest problem limiting the use of many anticancer drugs. The problem of how to kill cancer without harming a patient can be solved by using organic selenium (IV) compounds. Organic selenium (IV) compounds are a new class of materials showing a strong anticancer activity. They are first organic compounds containing selenium at the +4 oxidation level and therefore they eliminate the multidrug-resistance for all tumor cell lines tested so far. These materials are capable of selectively killing cancer cells without damaging the healthy ones. They are obtained by the incorporation of selenous acid (H2SeO3) into molecules of fatty acids of sunflower oil and therefore, they are inexpensive to manufacture. Attaching these compounds to magnetic carriers enables their precise delivery directly to the tumor area and the simultaneous application of the magnetic hyperthermia, thus creating a huge opportunity to effectively get rid of the tumor without any side effects. Polylactic-co-glicolic acid (PLGA) nanocapsules loaded with maghemite (-Fe2O3) nanoparticles and organic selenium (IV) compounds are successfully prepared by nanoprecipitation method. In vitro antitumor activity of the nanocapsules were evidenced using murine melanoma (B16-F10), oral squamos carcinoma (OSCC) and murine (4T1) and human (MCF-7) breast lines. Further exposure of these cells to an alternating magnetic field increased the antitumor effect of nanocapsules. Moreover, the nanocapsules presented antitumor effect while not affecting normal cells. Magnetic properties of the nanocapsules were investigated by means of dc magnetization, ac susceptibility and electron spin resonance (ESR) measurements. The nanocapsules presented a typical superparamagnetic behavior around room temperature manifested itself by the split between zero field-cooled/field-cooled (ZFC/FC) magnetization curves and the absence of hysteresis on the field-dependent magnetization curve above the blocking temperature. Moreover, the blocking temperature decreased with increasing applied magnetic field. The superparamagnetic character of the nanocapsules was also confirmed by the occurrence of a maximum in temperature dependences of both real ′(T) and imaginary ′′ (T) components of the ac magnetic susceptibility, which shifted towards higher temperatures with increasing frequency. Additionally, upon decreasing the temperature the ESR signal shifted to lower fields and gradually broadened following closely the predictions for the ESR of superparamagnetoc nanoparticles. The observed superparamagnetic properties of nanocapsules enable their simple manipulation by means of magnetic field gradient, after introduction into the blood stream, which is a necessary condition for their use as magnetic drug carriers. The observed anticancer and superparamgnetic properties show that the magnetic nanocapsules loaded with organic selenium (IV) compounds should be considered as an effective material system for magnetic drug delivery and magnetohyperthermia inductor in antitumor therapy.

Keywords: cancer treatment, magnetic drug delivery system, nanomaterials, nanotechnology

Procedia PDF Downloads 180
1609 Design Study for the Rehabilitation of a Retaining Structure and Water Intake on Site

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 323
1608 An Improved Total Variation Regularization Method for Denoising Magnetocardiography

Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

Procedia PDF Downloads 128
1607 Selective Circular Dichroism Sensor Based on the Generation of Quantum Dots for Cadmium Ion Detection

Authors: Pradthana Sianglam, Wittaya Ngeontae

Abstract:

A new approach for the fabrication of cadmium ion (Cd2+) sensor is demonstrated. The detection principle is based on the in-situ generation of cadmium sulfide quantum dots (CdS QDs) in the presence of chiral thiol containing compound and detection by the circular dichroism spectroscopy (CD). Basically, the generation of CdS QDs can be done in the presence of Cd2+, sulfide ion and suitable capping compounds. In addition, the strong CD signal can be recorded if the generated QDs possess chiral property (from chiral capping molecule). Thus, the degree of CD signal change depends on the number of the generated CdS QDs which can be related to the concentration of Cd2+ (excess of other components). In this work, we use the mixture of cysteamine (Cys) and L-Penicillamine (LPA) as the capping molecules. The strong CD signal can be observed when the solution contains sodium sulfide, Cys, LPA, and Cd2+. Moreover, the CD signal is linearly related to the concentration of Cd2+. This approach shows excellence selectivity towards the detection of Cd2+ when comparing to other cation. The proposed CD sensor provides low limit detection limits around 70 µM and can be used with real water samples with satisfactory results.

Keywords: circular dichroism sensor, quantum dots, enaniomer, in-situ generation, chemical sensor, heavy metal ion

Procedia PDF Downloads 345
1606 Performance Evaluation of Refinement Method for Wideband Two-Beams Formation

Authors: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

Procedia PDF Downloads 203
1605 55 dB High Gain L-Band EDFA Utilizing Single Pump Source

Authors: M. H. Al-Mansoori, W. S. Al-Ghaithi, F. N. Hasoon

Abstract:

In this paper, we experimentally investigate the performance of an efficient high gain triple-pass L-band Erbium-Doped Fiber (EDF) amplifier structure with a single pump source. The amplifier gain and noise figure variation with EDF pump power, input signal power and wavelengths have been investigated. The generated backward Amplified Spontaneous Emission (ASE) noise of the first amplifier stage is suppressed by using a tunable band-pass filter. The amplifier achieves a signal gain of 55 dB with low noise figure of 3.8 dB at -50 dBm input signal power. The amplifier gain shows significant improvement of 12.8 dB compared to amplifier structure without ASE suppression.

Keywords: optical amplifiers, EDFA, L-band, optical networks

Procedia PDF Downloads 321
1604 Time Delay Estimation Using Signal Envelopes for Synchronisation of Recordings

Authors: Sergei Aleinik, Mikhail Stolbov

Abstract:

In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided.

Keywords: cross-correlation, delay estimation, signal envelope, signal processing

Procedia PDF Downloads 459
1603 Energy Efficient Autonomous Lower Limb Exoskeleton for Human Motion Enhancement

Authors: Nazim Mir-Nasiri, Hudyjaya Siswoyo Jo

Abstract:

The paper describes conceptual design, control strategies, and partial simulation for a new fully autonomous lower limb wearable exoskeleton system for human motion enhancement that can support its weight and increase strength and endurance. Various problems still remain to be solved where the most important is the creation of a power and cost efficient system that will allow an exoskeleton to operate for extended period without batteries being frequently recharged. The designed exoskeleton is enabling to decouple the weight/mass carrying function of the system from the forward motion function which reduces the power and size of propulsion motors and thus the overall weight, cost of the system. The decoupling takes place by blocking the motion at knee joint by placing passive air cylinder across the joint. The cylinder is actuated when the knee angle has reached the minimum allowed value to bend. The value of the minimum bending angle depends on usual walk style of the subject. The mechanism of the exoskeleton features a seat to rest the subject’s body weight at the moment of blocking the knee joint motion. The mechanical structure of each leg has six degrees of freedom: four at the hip, one at the knee, and one at the ankle. Exoskeleton legs are attached to subject legs by using flexible cuffs. The operation of all actuators depends on the amount of pressure felt by the feet pressure sensors and knee angle sensor. The sensor readings depend on actual posture of the subject and can be classified in three distinct cases: subject stands on one leg, subject stands still on both legs and subject stands on both legs but transit its weight from one leg to other. This exoskeleton is power efficient because electrical motors are smaller in size and did not participate in supporting the weight like in all other existing exoskeleton designs.

Keywords: energy efficient system, exoskeleton, motion enhancement, robotics

Procedia PDF Downloads 350
1602 Uplink Throughput Prediction in Cellular Mobile Networks

Authors: Engin Eyceyurt, Josko Zec

Abstract:

The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

Procedia PDF Downloads 132
1601 Application of Local Mean Decomposition for Rolling Bearing Fault Diagnosis Based On Vibration Signals

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

Procedia PDF Downloads 367
1600 A Contactless Capacitive Biosensor for Muscle Activity Measurement

Authors: Charn Loong Ng, Mamun Bin Ibne Reaz

Abstract:

As elderly population grows globally, the percentage of people diagnosed with musculoskeletal disorder (MSD) increase proportionally. Electromyography (EMG) is an important biosignal that contributes to MSD’s clinical diagnose and recovery process. Conventional conductive electrode has many disadvantages in the continuous EMG measurement application. This research has design a new surface EMG biosensor based on the parallel-plate capacitive coupling principle. The biosensor is developed by using a double-sided PCB with having one side of the PCB use to construct high input impedance circuitry while the other side of the copper (CU) plate function as biosignal sensing metal plate. The metal plate is insulated using kapton tape for contactless application. The result implicates that capacitive biosensor is capable to constantly capture EMG signal without having galvanic contact to human skin surface. However, there are noticeable noise couple into the measured signal. Post signal processing is needed in order to present a clean and significant EMG signal. A complete design of single ended, non-contact, high input impedance, front end EMG biosensor is presented in this paper.

Keywords: contactless, capacitive, biosensor, electromyography

Procedia PDF Downloads 431
1599 Clove Oil Incorporated Biodegradable Film for Active Food Packaging

Authors: Shubham Sharma, Sandra Barkauskaite, Brendan Duffy, Swarna Jaiswal, Amit K. Jaiswal

Abstract:

Food packaging protects food from temperature, light, and humidity; preserves food and guarantees the safety and the integrity of the food. Advancement in packaging research leads to development of active packaging system with numerous properties such as oxygen scavengers, carbon-dioxide generating systems, antimicrobial active packaging, moisture control packaging, ethylene scavengers etc. In the active packaging, several additives such as essential oils, polyphenols etc. are incorporated into packaging film or within the packaging material to achieve the desired properties. This study investigates the effect on the structural, thermal and functional properties of different poly(lactide) – poly (butylene adipate-co-terephthalate) (PLA-PBAT) blend films incorporated with clove essential oil. The PLA-PBAT films were prepared by a solution casting method and then characterized based on their optical, mechanical properties, surface hydrophobicity, chemical composition, antimicrobial activity against S. aureus and E. coli, and inhibition of biofilm formation of E. coli. Results showed that, the developed packaging film containing clove oil has significant UV-blocking property (80%). However, incorporation of clove oil resulted in reduced transparency and tensile strength of the film as the concentration of clove oil increased. The surface hydrophobicity of packaging film was improved with the increasing concentration of essential oil. Similarly, thickness of the clove oil containing films increased from 36.71 µm to 106.67 µm as the concentration increases. The antimicrobial activity and biofilm inhibition study showed that the clove-incorporated PLA-PBAT composite film was effective against tested bacteria E. coli and S. aureus. This study showed that the PLA-PBAT – Clove oil composite film has significant antimicrobial and UV-blocking properties and can be used as an active food packaging film.

Keywords: active packaging, clove oil, poly(butylene adipate-co-terephthalate), poly(lactide)

Procedia PDF Downloads 128
1598 Forensic Speaker Verification in Noisy Environmental by Enhancing the Speech Signal Using ICA Approach

Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik

Abstract:

We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.

Keywords: noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping

Procedia PDF Downloads 385
1597 Study of Electro Magnetic Acoustic Transducer to Detect Flaw in Pipeline

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electro Magnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, NDT, artificial defect, ultrasonic testing

Procedia PDF Downloads 443
1596 Frequency-Dependent and Full Range Tunable Phase Shifter

Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang

Abstract:

In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz2/3 and 72.11 dB·Hz2/3 under different RF powers.

Keywords: microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent

Procedia PDF Downloads 256
1595 Optimal Mother Wavelet Function for Shoulder Muscles of Upper Limb Amputees

Authors: Amanpreet Kaur

Abstract:

Wavelet transform (WT) is a powerful statistical tool used in applied mathematics for signal and image processing. The different mother, wavelet basis function, has been compared to select the optimal wavelet function that represents the electromyogram signal characteristics of upper limb amputees. Four different EMG electrode has placed on different location of shoulder muscles. Twenty one wavelet functions from different wavelet families were investigated. These functions included Daubechies (db1-db10), Symlets (sym1-sym5), Coiflets (coif1-coif5) and Discrete Meyer. Using mean square error value, the significance of the mother wavelet functions has been determined for teres, pectorals, and infraspinatus around shoulder muscles. The results show that the best mother wavelet is the db3 from the Daubechies family for efficient classification of the signal.

Keywords: Daubechies, upper limb amputation, shoulder muscles, Symlets, Coiflets

Procedia PDF Downloads 217
1594 Denoising Transient Electromagnetic Data

Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

Abstract:

Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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1593 Traffic Signal Control Using Citizens’ Knowledge through the Wisdom of the Crowd

Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

Abstract:

Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

Procedia PDF Downloads 88
1592 Low Cost Surface Electromyographic Signal Amplifier Based on Arduino Microcontroller

Authors: Igor Luiz Bernardes de Moura, Luan Carlos de Sena Monteiro Ozelim, Fabiano Araujo Soares

Abstract:

The development of a low cost acquisition system of S-EMG signals which are reliable, comfortable for the user and with high mobility shows to be a relevant proposition in modern biomedical engineering scenario. In the study, the sampling capacity of the Arduino microcontroller Atmel Atmega328 with an A/D converter with 10-bit resolution and its reconstructing capability of a signal of surface electromyography are analyzed. An electronic circuit to capture the signal through two differential channels was designed, signals from Biceps Brachialis of a healthy man of 21 years was acquired to test the system prototype. ARV, MDF, MNF and RMS estimators were used to compare de acquired signals with physiological values. The Arduino was configured with a sampling frequency of 1.5 kHz for each channel, and the tests with the circuit designed offered a SNR of 20.57dB.

Keywords: electromyography, Arduino, low-cost, atmel atmega328 microcontroller

Procedia PDF Downloads 338
1591 Single Chip Controller Design for Piezoelectric Actuators with Mixed Signal FPGA

Authors: Han-Bin Park, Taesam Kang, SunKi Hong, Jeong Hoi Gu

Abstract:

The piezoelectric material is being used widely for actuators due to its large power density with simple structure. It can generate a larger force than the conventional actuators with the same size. Furthermore, the response time of piezoelectric actuators is very short, and thus, it can be used for very fast system applications with compact size. To control the piezoelectric actuator, we need analog signal conditioning circuits as well as digital microcontrollers. Conventional microcontrollers are not equipped with analog parts and thus the control system becomes bulky compared with the small size of the piezoelectric devices. To overcome these weaknesses, we are developing one-chip micro controller that can handle analog and digital signals simultaneously using mixed signal FPGA technology. We used the SmartFusion™ FPGA device that integrates ARM®Cortex-M3, analog interface and FPGA fabric in a single chip and offering full customization. It gives more flexibility than traditional fixed-function microcontrollers with the excessive cost of soft processor cores on traditional FPGAs. In this paper we introduce the design of single chip controller using mixed signal FPGA, SmartFusion™[1] device. To demonstrate its performance, we implemented a PI controller for power driving circuit and a 5th order H-infinity controller for the system with piezoelectric actuator in the FPGA fabric. We also demonstrated the regulation of a power output and the operation speed of a 5th order H-infinity controller.

Keywords: mixed signal FPGA, PI control, piezoelectric actuator, SmartFusion™

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1590 Aliasing Free and Additive Error in Spectra for Alpha Stable Signals

Authors: R. Sabre

Abstract:

This work focuses on the symmetric alpha stable process with continuous time frequently used in modeling the signal with indefinitely growing variance, often observed with an unknown additive error. The objective of this paper is to estimate this error from discrete observations of the signal. For that, we propose a method based on the smoothing of the observations via Jackson polynomial kernel and taking into account the width of the interval where the spectral density is non-zero. This technique allows avoiding the “Aliasing phenomenon” encountered when the estimation is made from the discrete observations of a process with continuous time. We have studied the convergence rate of the estimator and have shown that the convergence rate improves in the case where the spectral density is zero at the origin. Thus, we set up an estimator of the additive error that can be subtracted for approaching the original signal without error.

Keywords: spectral density, stable processes, aliasing, non parametric

Procedia PDF Downloads 109