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The subject of this study is a frequency estimation algorithm suitable for grid-connected power converters placed at a weak coupling point of a three-phase electrical distribution system. An upgraded version of the widely used complex least mean squares (CLMS) algorithm for frequency estimation is introduced to cope with different voltage amplitude unbalance and harmonic distortion levels, both frequently present in power system at distribution level. First, it is suggested that the CLMS algorithm uses only a positive phase-sequence component of voltage vector, the component that is inherently symmetrical and by cancelling the phase unbalance preserves the circular vector trajectory in a two-phase αβ-plane. This study shows that it is even possible to use the positive voltage phase-sequence vector extracted using a constant delay block, thus avoiding potential instability issues in the case of signal frequency feedback loop. Second, possible high signal harmonics and signal measurement noise are both removed using low-pass filters prior to CLMS algorithm deployment. Computer simulations and experiments are performed under a variety of conditions to validate the effectiveness of the proposed technique. Experimental results are achieved using the dataset sampled from the actual three-phase grid voltage at distributed level and with data processing done in the LabVIEW software environment.

LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) developed by National Instruments is a graphical programming environment.Its ease of use allows engineers and students to streamline the creation of code visually, leaving time traditionally spent on debugging for true comprehension of DSP.

The paper considers the features of constructing an information model of the human peripheral auditory system in the LabVIEW software environment. A brief description of the adopted information model proposed for implementation in the software environment is given. Detailed explanations are described for each element of the model made in the LabVIEW environment. The main functionality of the user part of the program is presented. The work is, in fact, staged in nature and offers a sequence of further necessary studies of the developed model.

Transformer load losses cause various adverse effects, such as derating, a decreased lifetime, and greenhouse gas emissions. In this paper, the load losses caused by non-linear loads on distribution transformers are analyzed. For this study, the load loss expressions provided by the IEEE Standard C57.110 and ANSI/UL 1561-1562 were adapted to the usual case where the transformer currents differ in each phase. The novel load loss expressions adapted from the IEEE Standard C57.110 were applied using the software known as the “Transformer Loss Calculator” (TLC), implemented with LabVIEW. For the application of new load loss expressions, carbon dioxide (CO2) emissions were determined by multiplying the load losses by the emission factors of each country. The experimental results are based on the recordings made by a FLUKE 435 Series II analyzer on the second of two 1000 kVA transformers, feeding real residential distribution networks with very differently distorted loads. An analysis of these transformers shows that the annual energy losses and CO2 emissions obtained from the adapted load loss expressions could be more than 5% of those determined by the original IEEE and ANSI Standard expressions. Due to these percentage loss and emission differences, it is advisable to use the TLC software in transformer monitoring instruments.

The utilization of heart Electrocardiograms (ECGs) is to measure irregular heart rate and regularity and detection of an arrhythmia. Various ways are submitted and utilized for cardiogram feature extraction with a reasonable percentage of right detection. Although the problem stays open, especially with respect to superior detection accuracy in ECGs. In nature, The ECG signals are very sensitive signals, having voltage-level as low as 0.5-5 mv and frequency-elements fall into the range of 0.05-100Hz and the largest amount of the information received in the range of 0.05-45Hz. The recorded ECG signal includes various kinds of noises such as baseline wander, channel noise which becomes very critical to eliminating for the best clinical finding which assists in the patient. The utilization of the discrete wavelet transform (DWT) as wavelet transforms can be utilized to be a two-dimensional time scale process technique for feature extraction and classification task, therefore it's appropriate for the non- stationary ECG signals (because of the sufficient range values and the shift in a timely) in LabVIEW. To implement the feature extraction and classification tasks, a separating wavelet transformation (consonant), and the wavelet transform can be two-dimensional time-scale practical technique was utilized. Hence, it is relevant for non-constant ECG signals (because of sufficient scale-values and transformation in timely) in LabVIEW. The flexibility, standard nature and simplicity to utilizing programming possible with LabVIEW, makes it less complex. The pro-posed algorithm is executed in two steps. First step, de-noises the signal from the cardiogram signal to get rid of the noise, then detects the pulse, our extracted parameters are heart rate, P wave amplitude, T wave amplitude, S value, Q value, R-value, P offset location, P onset location, T onset location, T offset location and the location of P, Q, R, S and T wave.

This study presents an electrocardiogram (ECG) monitoring and processing system which can observe subjects in real time and display the resultant ECG signals on a computer for observation. The primary application is for the remote observation of cardiac patients. This paper aims to determine its reliability by analysing its portability and wireless connectivity. The system is comprised of three principal units, namely the data acquisition circuit, where cardiac electrical signals are detected using three surface electrodes placed at three different positions on the chest wall to follow the Einthoven Triangle. The signals measured are amplified and filtered by components in a circuit and are then carried to a data processing unit where a ATmega328P microcontroller with a ZigBee interface module are used to transfer the biosignal wirelessly to the Graphical User Interface (GUI) unit which has the capacity to observe ECG biosignals on a computer. The results demonstrated that the design successfully produced a distortion-free signal, namely the hardware and software elements operated and intercommunicated correctly. In both LabVIEW and MATLAB configurations, the GUI characteristics were examined and found to yield unproblematic, user-friendly displays in real-time. Thus, this research provides a novel ECG system design to effectively analyse cardiac patients, however, it would be useful to develop a tool that can differentiate the various forms of cardiac arrhythmia.

This paper presents an implementation of a data acquisition system for analog-to-digital converters (ADCs) using “Laboratory Virtual Instrument Engineering Workbench (LabVIEW)” as software for data analysis. The designed and implemented platform allows interaction with the device under test through means of data acquisition and instrument controls. Developing custom tests in LabVIEW can result in reduced test time, which in turn will help reduce costs in testing. This system was developed for evaluation purposes of ADC's static and dynamic parameters (gain error, offset error, DNL, INL, SNR, SINAD, IMD, etc.) using single and multi-frequency signals. The virtual control and analysis instrument was created in “LabVIEW” environment to control test signals generation and data acquisition. The testing performance of the platform is demonstrated using the classical ADC circuit “ADC0804”. A comparison with experimental results obtained by CANTEST platform from Bordeaux University (France) is also presented to highlight our platform.

This article describes how physiological signal monitoring plays an important role in identifying the health condition of heart. In recent years, online monitoring and processing of biomedical signals play a major role in accurate clinical diagnosis. Therefore, there is a requirement for the developing of online monitoring systems that will be helpful for physicians to avoid mistakes. This article focuses on the method for real time acquisition of an ECG and PPG signal and it's processing and monitoring for tele-health applications. This article also presents the real time peak detection of ECG and PPG for vital parameters measurement. The implementation and design of the proposed wireless monitoring system can be done using a graphical programming environment that utilizes less power and a minimized area with reasonable speed. The advantages of the proposed work are very simple, low cost, easy integration with programming environment and continuous monitoring of physiological signals.

In this paper we present a way to use the open-source electronic platforms that are programmed through LabVIEW graphical programming environment. The application that is made is a programmable instrument used for measuring the short distances based on time of flight of sound waves in an environment with known propagation properties. Based of obtained results are made assessments on the quality of information obtained.

It is important to analyze the current state of a person during respiration in individual breathing apparatus. For that reason, you need to register cardiorespiratory parameters of a human. Reusable simulators of breathing apparatus with specific hardware and software are used for these purposes. They allow simulating the conditions of the breathing, equivalent to primary breathing apparatus with chemically bound oxygen. During the development of the mine insulating self-rescuer simulator for the personnel of mining industries, the indicators of heart rate variability, spirography and pneumotachography were identified. Based on the analysis of the requirements in the recorded parameters, a selection of control devices and measuring sensors was carried out, a diagram of the simulator hardware was developed, and information flows were formalized. The graphic programming environment LabVIEW was selected as development environment. The paper presents the structure and functioning algorithms of the main program control units of the simulator which responsible for the generation of the specified breathing conditions