scholarly journals Development of Real Time Power Quality (RTPQ) Analyzer using Lab-VIEW

2019 ◽  
Vol 8 (3) ◽  
pp. 458-464
Keyword(s):  
Real Time ◽  
Power Quality ◽  
Real Life ◽  
Electric Energy ◽  
Optimal Solution ◽  
Test System ◽  
Quality Analysis ◽  
Time Data ◽  
Major Drawback ◽  
Lab View

Power Quality (PQ) issues and its alleviation techniques are becoming one of the vital research topics, soon after the integration of power electronic devices in power system. The non-linear nature of equipment’s introduces PQ issues such as voltage sag, swell, harmonics, unbalance and transients etc. and cause damage of end user equipment’s. Poor PQ has become a vital issue which affects production and profit of both utilities and consumers. Therefore continuous monitoring and assessment of PQ is essential for finding optimal solution to analyze and mitigate various PQ problems and also maintain quality of power within the prescribed limit. For PQ analysis, it is very difficult to generate power quality events in real life in order to observe the effects or to study their characteristics. Now days, various physical PQ analyzers are available in market to continuously monitor, analyze and record PQ problems. The major drawback of this analyzer is its hardware design, complexity and its cost which limits its usage to many places. Thus online PQ monitoring is a very big challenge for researches. This paper presents modeling and simulation of virtual PQ analyzer using Lab VIEW. Lab VIEW supports a lot of library functions for an acquisition, analysis of data and also the control of instruments. This software is mainly used to model standard real instruments used in laboratories by providing more flexibility. The proposed PQ analyzer is capable of generating, identifying various PQ problems and also measuring PQ parameters RMS Voltage (Vrms), RMS Current (Irms), Total Harmonic Distortion (THD), Real, Reactive and Apparent Power from the test system. Using Lab VIEW software, a complete quality analysis of electric energy can be done online at the user's location. So that the selection of custom power devices and mitigation methods for PQ problems can be done in a perfect manner. This RTPQ analyzer is tested using real time data of hardware are acquired by the construction of test systems such as rectifier with various resistive and inductive loads. ALL PQ parameters measured using proposed PQ Analyzer are also compared with the parameters measured using fluke PQ Analyzer. The response attained has proven that the accuracy and precision of the proposed analyzer can also be used as a very good cost effective tool for online PQ study.

Ambulatory Assessment

2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull
Keyword(s):  
Real Time ◽  
Clinical Psychology ◽  
Real Life ◽  
Ambulatory Assessment ◽  
Computer Assisted ◽  
Affective Valence ◽  
Time Data ◽  
Physiological Processes ◽  
Context Specific ◽  
Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

Big Data Management in the Context of Real-Time Data Warehousing

2013 ◽  
pp. 150-176
Author(s):  
M. Asif Naeem ◽  
Gillian Dobbie ◽  
Gerald Weber
Keyword(s):  
Big Data ◽  
Data Integration ◽  
Real Time ◽  
Real Life ◽  
Skewed Distribution ◽  
Stream Data ◽  
Time Data ◽  
Master Data ◽  
Real Time Data ◽  
Resource Aware

In order to make timely and effective decisions, businesses need the latest information from big data warehouse repositories. To keep these repositories up to date, real-time data integration is required. An important phase in real-time data integration is data transformation where a stream of updates, which is huge in volume and infinite, is joined with large disk-based master data. Stream processing is an important concept in Big Data, since large volumes of data are often best processed immediately. A well-known algorithm called Mesh Join (MESHJOIN) was proposed to process stream data with disk-based master data, which uses limited memory. MESHJOIN is a candidate for a resource-aware system setup. The problem that the authors consider in this chapter is that MESHJOIN is not very selective. In particular, the performance of the algorithm is always inversely proportional to the size of the master data table. As a consequence, the resource consumption is in some scenarios suboptimal. They present an algorithm called Cache Join (CACHEJOIN), which performs asymptotically at least as well as MESHJOIN but performs better in realistic scenarios, particularly if parts of the master data are used with different frequencies. In order to quantify the performance differences, the authors compare both algorithms with a synthetic dataset of a known skewed distribution as well as TPC-H and real-life datasets.

Research on Boom-Type Roadheader Vibration Testing Based on the LabVIEW

2011 ◽  
Vol 418-420 ◽  
pp. 1988-1991
Author(s):  
Li Juan Zhao ◽  
Xiu Mei Lv ◽  
Wei Tong
Keyword(s):  
Real Time ◽  
Detection System ◽  
Structural Characteristics ◽  
Test System ◽  
Vibration Characteristics ◽  
Acquisition Time ◽  
Vibration Source ◽  
Time Data ◽  
Vibration Signals ◽  
Time Frequency

This develops the roadheader vibration characteristics test system according to the structural characteristics and working principle of the cantilevered roadheader. Using the piezoelectric acceleration sensor detects vibration signal, and passing by signal processing and A/D conversion， vibration signals are sent to the PC with wireless transmission mode, vibration signals detected by the LabVIEW is realized real-time data acquisition, time-frequency analysis and digital processing. Based on this system testing results can effectively master roadheader operation state, identify the vibration characteristics, look for vibration source and put forward reasonable damping vibration measure, which provide the basis for roadheader in the best running condition. The development of roadheader vibration detection system uses the method that combines theory and simulation experiment , which realizes the real-time detection of roadheader vibration behavior, rational signal analysis of roadheader vibration and accurate processing of data results, it provides an important method to ensure the reliability of roadheader.

Smart Environmental Monitoring System

2019 ◽  
Vol 10 (1) ◽  
pp. 43-54
Author(s):  
Karthik Sudhakaran Menon ◽  
Brinzel Rodrigues ◽  
Akash Prakash Barot ◽  
Prasad Avinash Gharat
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Urban Areas ◽  
Real Life ◽  
Cloud Service ◽  
Threshold Value ◽  
Time Data ◽  
Multiple Sensors ◽  
Alert Message ◽  
Environmental Monitoring System

In today's world, air pollution has become a common phenomenon everywhere, especially in the urban areas, air pollution is a real-life problem. In urban areas, the increased number of hydrocarbons and diesel vehicles and the presence of industrial areas at the outskirts of the major cities are the main causes of air pollution. The problem is seriously intense within the metropolitan cities. The governments around the world are taking measure in their capability. The main aim of this project is to develop a system which may monitor and measure pollutants in the air in real time, tell the quality of air and log real-time data onto a remote server (Cloud Service). If the value of the parameters exceeds the given threshold value, then an alert message is sent with the GPS coordinates to the registered number of the authority or person so necessary actions can be taken. The Arduino board connects with Thingspeak cloud service platform using ESP8266 Wi-Fi module. The device uses multiple sensors for monitoring the parameters of the air pollution like MQ-135, MQ-7, DHT-22, sound sensor, LCD.

Real-Time Dispatching Operation Risk Assessment Based on Fault Tree Theory

2013 ◽  
Vol 732-733 ◽  
pp. 909-914
Author(s):  
En Wang ◽  
Wei Wei ◽  
Bing Dong Wang ◽  
Zhe Liu
Keyword(s):  
Real Time ◽  
Fault Tree ◽  
Test System ◽  
Control Measures ◽  
Risk Level ◽  
Time Data ◽  
Risk Indices ◽  
Risk Sources ◽  
Line Overload ◽  
Operation Risk

Reasonable dispatching strategies are important to guarantee secure and reliable operation of power system. Now the operators use real-time data and their experience to dispatch the system, but the huge data system brings much inconvenience to operators. In this paper, the risk theory is introduced into dispatching operation quantitative assessment, and a real-time dispatching operation risk analysis method is proposed. Fault tree is used to simulate dispatching operation process and comprehensively analyze the system risk in both under-successful and failure state of the operation. Risk indices are given to quantitatively reflect the risk level of each operation step based on local information, such as voltage out-of-limit risk, line overload risk, load curtailment risk, so that the operators can clearly recognize the risk and risk sources in each operation step and take corresponding pre-control measures. Finally, the effectiveness and practicability of proposed method is validated by an IEEE RTS test system.

scholarly journals Development of a Measuring Sensory System Based on LabVIEW for Determining Elastic Proprieties of Solid Materials

2016 ◽  
Vol 6 (5) ◽  
pp. 2096
Author(s):  
Zakaryae Ezzouine ◽  
Abdelrhani Nakheli
Keyword(s):  
Tensile Test ◽  
Real Time ◽  
Low Cost ◽  
Sensory System ◽  
Test System ◽  
Model Parameters ◽  
Time Data ◽  
Solid Materials ◽  
Measuring Device ◽  
Deformation Curves

<p>This article develops also a measure and prototype to allow the acquisition of real time data for display, analysis, control and storage with a proposed test program for determining the model parameters. The aim is to be able to measure, and apply moment to a specimen, and collect data from the resulting deformation in the material. At the same time, the reliability of this test system has been proved by precision analysis and data processing for a simple test validation (metal wire). The force-deformation curves of solids materials in this tensile test are measured accurately in real time, to obtain the values of solid materials mechanical property parameters, The minimal change in length of the test Specimen that can be resolved by this system is 1µm, which yields the sensitivity comprised between 10-4µm and 10-5 µm. Based on the experience that compressive tensile test have the smallest statistical scatter and that they are simplest to carry out. The measuring device can improve the measuring efficiency and accuracy distinctly while has advantages of simple configuration, low cost and high stability.</p>

scholarly journals Real-Time Data Scheduling of Flexible Job in Papermaking Workshop Based on Deep Learning and Improved Fuzzy Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shihong Dang ◽  
Wei Tang
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Operating Cost ◽  
Optimal Solution ◽  
Time Data ◽  
Fuzzy Algorithm ◽  
Data Scheduling ◽  
Fuzzy Scheduling ◽  
Real Time Data ◽  
Scheduling Method

The traditional real-time data scheduling method ignores the optimization process of job data that leads to delayed delivery, high inventory cost, and low utilization rate of equipment. This paper proposes a novel real-time data scheduling method based on deep learning and an improved fuzzy algorithm for flexible operations in the papermaking workshop. The algorithm is divided into three parts: the first part describes the flexible job shop scheduling problem; the second part constructs the fuzzy scheduling model of flexible job data in papermaking workshop; and finally the third part uses a genetic algorithm to obtain the optimal solution of fuzzy scheduling of flexible job data in papermaking workshop. The results show that the optimal solution is obtained in 48 seconds at the 23rd attempt (iteration) under the application of the proposed method. This result is much better than the three traditional scheduling methods with which we compared our results. Hence, this paper improves the work efficiency and quality of papermaking workshop and reduces the operating cost of the papermaking enterprise.

Filter Implementation Using Output Transformer of UPS for Power Quality Improvement

2017 ◽  
Vol 8 (3) ◽  
pp. 1251
Author(s):  
Anandh N. ◽  
Pramod Antony D'Sa ◽  
M.V. Gautam ◽  
V.Sai Sandeep
Keyword(s):  
Quality Improvement ◽  
Power Electronics ◽  
Power Quality ◽  
Quality Analysis ◽  
Time Data ◽  
Non Linear ◽  
Power Quality Improvement ◽  
A New Technique ◽  
Non Linear Load ◽  
Output Transformer

Power electronics play a significant role in different areas of technology, more usage of power electronic devices lead to more harmonic content and various power quality issues in the system.  Therefore, power quality gains more significance in the current era of research. Power electronics equipment’s with non-linear loads concludes with more harmonic disturbances and lower power factor. Harmonic impurities are the major problem ingredient due to the connection of non-linear load. To lessen the harmonics usually passive filters are used. The major objective of this work is to monitor and analyse the power quality of uninterrupted power supply by means of DAQ system that gathers real time data on the system and then the data is analysed using National Instruments LabVIEW. Once power quality analysis is done, a new technique of filter implementation using output transformer of the UPS was explored and passive filter was simulated using MATLAB/Simulink and then simulated filter was implemented in order to achieve power quality improvement.

scholarly journals Improved real-time data anomaly detection using context classification

2011 ◽  
Vol 13 (3) ◽  
pp. 307-323 ◽  
Author(s):  
Nemanja Branisavljević ◽  
Zoran Kapelan ◽  
Dušan Prodanović
Keyword(s):  
Anomaly Detection ◽  
Data Acquisition ◽  
Real Time ◽  
Water Distribution ◽  
Real Life ◽  
Detection Methods ◽  
Time Data ◽  
Detection Techniques ◽  
Real Time Data ◽  
Processing Techniques

The number of automated measuring and reporting systems used in water distribution and sewer systems is dramatically increasing and, as a consequence, so is the volume of data acquired. Since real-time data is likely to contain a certain amount of anomalous values and data acquisition equipment is not perfect, it is essential to equip the SCADA (Supervisory Control and Data Acquisition) system with automatic procedures that can detect the related problems and assist the user in monitoring and managing the incoming data. A number of different anomaly detection techniques and methods exist and can be used with varying success. To improve the performance, these methods must be fine tuned according to crucial aspects of the process monitored and the contexts in which the data are classified. The aim of this paper is to explore if the data context classification and pre-processing techniques can be used to improve the anomaly detection methods, especially in fully automated systems. The methodology developed is tested on sets of real-life data, using different standard and experimental anomaly detection procedures including statistical, model-based and data-mining approaches. The results obtained clearly demonstrate the effectiveness of the suggested anomaly detection methodology.

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