Real-time Wavelet Analysis Research Articles

Modeling and Stability Analysis of an Active Islanding Detection Method in DC Microgrids Using Real-time Wavelet Analysis

Modeling and Stability Analysis of an Active Islanding Detection Method in DC Microgrids Using Real-time Wavelet Analysis

Detailed muscle state analysis method based on real-time wavelet analysis of surface myoelectric potential

Myoelectric refers to the use of electricity generated by muscles and is harnessed in the development of electrically powered prostheses, which are controlled by electromyographic (EMG) signals created in the residual musculature. Assistant professor Hidetoshi Nagai, Department of Artificial Intelligence, Kyushu Institute of Technology, Japan, is interested in surface myoelectric signals and is working on a project to develop technology that can advance their use. Nagai will capture motor unit activities using surface electromyography, which is easy to measure during exercise, and use this as the basis for more detailed muscle activity analysis. The methods Nagai has developed require no special equipment, other than the ability to sample at frequencies of several tens of kHz, and only require a single channel, which indicates the potential for more sophisticated analysis when multiple channels of information are present. It is also a simple and lightweight process that can be executed in real time. Conventional analysis and evaluation of muscle activity cannot be performed from the perspective of motor unit activity but Nagai has built on the basic premise that given that muscle activity is the sum of motor unit activities, the analysis of muscle activity should be based on the analysis of motor unit activity. He will analyse the surface EMG signal from the viewpoint of its component waveform the motor unit waveform so that muscle activity analysis can be performed as it should be.

Signal De-Noising of Quench Detection by Real-Time Wavelet Analysis Algorithm for HTS Coil and Magnet

For automatic quench protection system, correction of quench judgment is important to the prolonged stable operation of superconducting devices. In poor electromagnetic environment, quench detection based on electrometric method is easily interfered by noise and severely disrupted quench signal may cause wrong quench determination and malfunction of quench protection, thereby resulting in unnecessary loss. One reason causing noise is current fluctuation and the noise is hard to be filtered by conventional filter circuit. In order to restrain noise and reduce false action of quench detection, this paper proposes a real-time wavelet analysis algorithm based on field programmable gate array platform. Experiment of filtering noise coupled whit quench signal of a HTS coil shows that the real-time wavelet analysis algorithm can filter noise out effectively. This method can be applied for filtering noise of quench detection for HTS coil and magnet.

Real-Time Wavelet Analysis of a Vibration Signal Based on Arduino-UNO and LabVIEW

This paper deals with on-line (Real-time) multi- resolution signal analysis using wavelet transform by means of graphical programming using LabVIEW. A system for wavelet analysis has been designed based on Arduino-Uno board interfaced to LabVIEW. To achieve the interfacing LIFA has been used. Firstly, the noise from the signal was remove using wavelet transform, and then the de-noised signal analyzed to multi-level frequency bands. A Matlab code to do wavelet analysis was written in a Matlab script node in LabVIEW. To test this system, a vibration signal form robotic arm was captured and analyzed using this system, and the result utilized to establish if there is fault in the robot. The result showed that multi-resolution analysis can be achieved efficiently using this system and can be applied in many applications. 

A Novel Design of Traveling Wave Protection Device in EHV Transmission Lines Based-On ARM and FPGA

As it is difficult to realize the traveling wave protection principle based on wavelet analysis in microcomputer protection device, a new microcomputer protection architecture based on FPGA+ARM is put forward in this paper This architecture make full use of ARM to complete relay protection principle, communication and the realization of the man-machine interface for the powerful transaction processing ability, and make use of FPGA to complete complex real-time wavelet analysis by a logic circuit for the characteristics of FPGA in high speed real-time parallel computation. It proves in experiment that this scheme is a good solution for the realization of travelling wave protection.

Real-time electrogram analysis for monitoring coronary blood flow during human ventricular fibrillation: Implications for CPR

Effective chest compressions during prolonged ventricular fibrillation (VF) have been shown to increase the chances of successful defibrillation to a rhythm associated with a sustainable cardiac output. There is currently no effective method of recording the degree of antegrade coronary artery flow during chest compression in VF. This study sought to quantify the relationship between the antegrade coronary flow and the characteristics of human VF using near real-time wavelet-based electrocardiographic markers. VF experiments were conducted in 8 isolated human hearts. The Langendorff perfusion enabled different flow rates (perfusion) during VF, which allowed for the simulation of chest compression with different efficacies. After the initiation of VF, the hearts were maintained in ischemia (no flow) for 3 minutes, followed by a 2-minute reperfusion and defibrillation. The experiments were repeated at flows of 0%, 30%, and 100% of baseline perfusion, and volume-conducted surface electrograms were recorded and analyzed using continuous wavelet transform in 5-second frames. Near real-time wavelet features were derived that demonstrated significant differences in the multicomponent nature of VF signals and predicted perfusion rate characteristics for different flow rates (i.e., 0%, 30%, and 100%; P < .0006). A pattern classifier was trained using the feature values from 5 hearts, and the flow rates for 3 additional hearts were predicted with an accuracy of 90%. VF electrogram characteristics as measured by wavelet analysis relate to antegrade coronary flow rate during VF. These findings suggest that chest compression efficacy of physiological importance could be monitored using near real-time wavelet analysis.

Review of the ASDEX Upgrade data acquisition environment—present operation and future requirements

The data acquisition environment of the ASDEX Upgrade fusion experiment was designed in the late 1980s to handle a predicted quantity of 8 Mbytes of data per discharge. After 7 years of operation a review of the whole data acquisition and analysis environment shows what remains of the original design ideas. Comparing the original 15 diagnostics with the present set of 250 diagnostic datasets generated per shot shows how the system has grown. Although now a vast accumulation of functional parts, the system still works in a stable manner and is maintainable. The underlying concepts affirming these qualities are modularity and compatibility. Modularity ensures that most parts of the system can be modified without affecting others. Standards for data structures and interfaces between components and methods are the prerequisites which make modularity work. The experience of the last few years shows that, besides the standards achieved, new, mainly real-time, features are needed: real-time event recognition allowing reaction to complex changing conditions; real-time wavelet analysis allowing adapted sampling rates; real-time data exchange between diagnostics and control; real-time networks allowing flexible computer coupling to permit interplay between different components; object-oriented programming concepts and databases are required for readily adaptable software modules. A final assessment of our present data processing situation and future requirements shows that modern information technology methods have to be applied more intensively to provide the most flexible means to improve the interaction of all components on a large fusion device.

Wavelet analysis of embolic heart sound detected by precordial Doppler ultrasound during continuous venous air embolism in dogs.

The spectrum of the embolic heart sounds (EHS) detected by precordial Doppler ultrasound has been previously characterized, but only on small volumes of venous air embolism (VAE). We sought to determine whether real-time wavelet analysis is useful in analyzing the signals of EHS and whether the embolic power of the EHS for larger volumes of air is proportionate to the volume of VAE that has been reported for small volumes of VAE. A series of small air boli (0.01, 0.02, 0.05, 0.07, 0.1, 0.15, 0.2, 0.3, 0.4, and 0.8 mL), followed by continuous infusion of larger volumes of air (0.8, 1.6, 2.4, 4.8, and 9.6 mL), was injected into the external jugular vein through a central catheter in seven pentobarbital-anesthetized dogs. We measured the spectrum of the Doppler heart sound (DHS) in a real-time manner by using wavelet analysis at different scales. Wavelet analysis at scale = 1 yielded satisfactory results in distinguishing abnormal EHS from normal DHS with high sensitivity (100%) and good positive predictive value (100%) compared with the conventional method, which requires an anesthesiologist to listen to the audio DHS signals in a real-time manner. There was a linear relationship (y = 1.08x + 7.89, r = 0.75, P < 0.001) between the cumulative embolic power of the EHS and the air volume introduced in the form of either bolus or continuous infusion. The 95% confidence intervals for slope and intercept were 0.89-1.27 and 7.65-8.13, respectively. Our results suggest that wavelet analysis is effective as a real-time monitor and that it is possible to distinguish larger volumes of air emboli based on previous injections of small volumes of air. The real-time wavelet analysis of the heart sound detected by precordial Doppler ultrasound may be useful in estimating larger volumes of air emboli based on previous injections of small volumes of air in anesthetized dogs.