M. Kalyan Chakravarthi ¹, Nithya Venkatesan ¹

Affiliations
1 School of Electronics Engineering, VIT University, Chennai – 600127, Tamil Nadu, IN

Abstract

Objectives: This study aims at designing an easy and a secured way of remote server based data logging using a data acquisition mechanism and HFS (http File Server) software. Methods/Statistical Analysis: Lab VIEW based remote data monitoring and controlling system is designed so as to view and analyze the fidelity of the data. This mechanism proves to be a secured data logger providing an increased access to the users in the loop, along with time stampings and many other additional features. A real time nonlinear process system was considered as a bench mark system for the purpose of logging the level data of it remotely. The Dual Spherical Tank Liquid Level System (DSTLLS) has been chosen and its continuously varying liquid levels are recorded and monitored remotely over the LAN, using remote Master-Slave architecture and File Transfer Server. Findings: It was found that these methods of the data logging prove to be faster and cheaper when compared to the existing methods. Classical algorithmic approach for the data transfer is being applied to facilitate the data logging process. Application/Improvements: There is scope of performing experiments on the data transfer mechanisms using different algorithms and analyzing their performance and efficiency in data logging process.

Keywords

DPT, HTTP File Server HFS, Lab VIEW, Process control, Remote Control.

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M. Kalyan Chakravarthi ¹, Nithya Venkatesan ¹

Affiliations
1 School of Electronics Engineering, VIT University, Vandalur-Kelambakkam Road, Chennai - 600127, Tamil Nadu, IN

Abstract

Objectives: The process industries have always been in search of innovative ways of data logging mechanisms, for they happen to execute complicated flow mechanisms on a long span of time uninterruptedly. Data loggers in existence have contributed to a greater extent as assisting technology to store and monitor the data and also in rugged measurement environment. This study aims at designing an easy and a secured way of remote server based data logging using a data acquisition mechanism and HFS (http File Server) software. Methods/Statistical Analysis: LabVIEW based remote data monitoring and controlling system is designed so as to view and analyze the fidelity of the data. Findings: This mechanism proves to be a secured data logger providing an increased access to the users in the loop, along with time stampings and many other additional features. A real time nonlinear process system was considered as a bench mark system for the purpose of logging the level data of it remotely. The Two Interacting Spherical Tank Liquid Level System (TISTLLS) has been chosen and its continuously varying liquid levels are recorded and monitored remotely over the LAN, using remote Master-Slave architecture and File Transfer Server. It was found that these methods of the data logging prove to be faster and cheaper when compared to the existing methods. Classical algorithmic approach for the data transfer is being applied to facilitate the data logging process. Application/Improvements: There is scope of performing experiments on the data transfer mechanisms using different algorithms and analyzing their performance and efficiency in data logging process.

Keywords

DPT, HTTP File ServerHFS, LabVIEW, Process Control, Remote Control.

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John Sahaya Rani Alex ¹, Ajinkya Sunil Mukhedkar ¹, Nithya Venkatesan ¹

Affiliations
1 School of Electronics Engineering Department, VIT University, Chennai - 600 127, Tamil Nadu, IN

Abstract

Background: Speech recognition is an active area of research, used to transliterate words vocalized by individuals in order to make them machine recognizable. For real time speech recognition applications the response time, size of training data and recognition accuracy are the important aspects. Methods: A Hybrid speech recognition system is proposed on the basis on Artificial Neural Network (ANN) in this research. The Self Organising Feature Map (SOFM) is used to reduce the feature vector dimensions which are extracted using the Mel-Frequency Cepstrum Coefficients (MFCC), Perceptual Linear Predictive (PLP) and Discrete Wavelet Transform (DWT) methods. The Back Propagation Network (BPN) algorithm is used for training the Artificial Neural Network for pattern classification. Findings: The proposed method is tested with TIDIGITS data. Results indicate that despite of the large reduction in the feature vector dimensions the recognition accuracy obtained using SOFM technique is same as that of the recognition accuracy of the conventional methods. The response time is also fast and the data size of the input data is reduced considerably. The proposed hybrid system is further tested using multilingual isolated digit data.

Keywords

Artificial Neural Network, Discrete Wavelet Transform, Feature Extraction, Mel Frequency Cepstrum Co-efficients, Perceptual Linear Predictive, Self-organising Feature Map, Speech Recognition

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M. Kalyan Chakravarthi ¹, Pannem K. Vinay ¹, Nithya Venkatesan ²

Affiliations
1 School of Electronics Engineering, VIT University, Chennai–600127, IN
2 School of Electrical Engineering, VIT University, Chennai–600127, IN

Abstract

Background/Objectives: PID controllers are one of the first solutions often considered in the control of process industries. It has always been very difficult to treat the level anomalies n the real time processes. Particularly the non linear systems and processes have been a challenge in relation with their dynamics and flow properties. Methods/Statistical analysis: Dual Spherical Tank Liquid Level System (DSTLLS) has the characteristics of nonlinearity due to the dynamic behaviour and area of cross section of tank. One of the major problems in process industries is to control of liquid level for Second Order System Plus Delay (SOSPD) system because the presence of time delay in the system can lead to destabilization of the system. This simulation aims at portraying the performance of the designed Internal Model Control (IMC) PID Controller. Using the black box modelling technique the SOSPD is mathematically modelled experimentally, assuming the system to be a Single Input Single Output (SISO) model. Findings: The aim of this paper is to design a PID controller using IMC tuning method for a (DSTLLS) whose modelling has been done in real time. This simulation briefly explains about stabilizing problem for SOSPD system using an IMC PID controller. The designed controller performance is analysed in terms of performance indices like Integral Squared Error (ISE) and Integral Absolute Error (IAE) and time domain specifications like Rise time, Settling time and Peak time. Conclusion: The validation of the performance of the designed controller is performed under MATLAB environment. There can different controllers which can be also experimented on the same mathematical model for different configurations of the system, namely MISO and MIMO.

Keywords

Internal Model Control (IMC), MATLAB, Non Linear Systems, SISO, Spherical Tank Systems

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Shreyas Patel ¹, John Sahaya Rani Alex ¹, Nithya Venkatesan ¹

Affiliations
1 School of Electronics Engineering, VIT University, Chennai - 600127, Tamil Nadu, IN

Abstract

Background/Objectives: Recent research focuses on low-power design techniques. This has been mainly inspired by the demand of hand-held electronic devices which have to consume less power. Neural network based classifiers are widely used in speech recognition which needs higher power. Methods/Statistical Analysis: A hybrid approach for designing architecture of Multi-Layer Perceptron (MLP) based Neural Network (NN) for speech recognition is proposed using bipartite tabular method and banking organization method. This approach is prototyped in Xilinx xc3s1200. The Back propagation neural network is trained in MATLAB using TIDIGITS corpus. Using the optimized weights from MATLAB, the proposed prototyped low-power architecture is evaluated in Xilinx. Findings: The outcome shows a considerable reduction both in area and power. Conclusion/Improvements: The reduction in switching power is by 33% and the average power is by 25% are noted. There was 2% reduction in the resources used by the proposed architecture.

Keywords

Banking Organization Method, Bipartite Tabular Method, Low Power Architecture, Multi-Layer Perceptron Neural Network, Speech Recognition

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