»  Projects

INTELLIGENT VOICE ASSIST DRIVING SYSTEMS (IVADS) USING LABVIEW
Blessy Mariam Markose*, Jyothi R Vijay*, Reena Varghese*, Shruthi Venugopal*
Under the Guidance of: Prof.P.S.Godwin Anand
Project carried out at: SAINTGITS Lab VIEW Academy, Kottayam, kerala

ABSTRACT

In recent years, due to advancement in engineering and technology, automobile industries have developed to a great extent. Today, many control applications systems such as automatic transmissions, engine control, ABS, climate control   system, etc., were successfully implemented. These systems make the drive safe with less strain to the driver. To add a feather to this crown of inventions, this project deals with the intelligent voice assist driving system. This system indicates in terms of visual and audio and it communicates to the driver about the driving efficiency, necessary gear shifts and about the safety warnings.  This project mainly focuses on manual transmission vehicles to improve the driving and fuel efficiency which may add life to engine. This technique is based on artificial intelligence, which compares the running gear, vehicle speed, fuel consumption, engine RPM and load in the vehicle. Based on the comparisons the intelligent system will assist the driver to shift the gear.  It also informs the driver about driving efficiency, speed, mileage etc., when asked for. Instead of producing an identical beep sound for various reasons, the voice assist informs what the exact problem is. To add more intelligence in the vehicle security system an additional biometric system can be integrated to start the vehicle. Also, in case of any collision, an emergency call is made to the hotline numbers provided, passing a pre-recorded message along with the geographical location of the car.  The entire concept is implemented using LabVIEW RTplatform.

INFILTRON-AN AUTONOMOUS ROBOT
Githin Sajeev George*, Greena Kuriakose*, Sreedevi S*,Toby James Thomas*
*Final Year Students,Department of Applied Electronics &Instrumentation,  SAINTGITS
Under the Guidance of: Prof.P.S.Godwin Anand
Project carried out at: SAINTGITS Lab VIEW Academy, Kottayam, kerala

ABSTRACT

This project presents Infiltron, an autonomous robot designed for military operations.  With increasing threats from the neighboring countries and within, the need for a substitute to human soldiers has alarmingly arisen. In war field many situations prevail where the enemy status have to be spied on and where human access is limited. In this project the robot is incorporated with different sensors, which are used to sense the target. It must have good sensing ability as it has to undergo diverse conditions. The different sensors to be used are sound sensors, thermal sensors and ultrasonic sound sensors.  Along with sensing, the images processing has to be carried out. This sensed information is transmitted to the controller, normally a human being who is at a safe location through wireless communication. This information is analyzed by the controller and decisions are implemented using remote controlling. After receiving the inputs, identification of target, understanding of commands and executing control actions has to done. This is done using algorithm in LabVIEW.

WEB BASED SPEED CONTROL OF A DC MOTOR USING LABVIEW
 Neelima G Sekhar,Sruthy S Nampoothiri, Stephy Mariam Varghese
*Final Year Students, Department of Applied Electronics &Instrumentation,  SAINTGITS
Under the guidance of: Prof. P.S. Godwin Anand
Project carried out at: SAINTGITS LabVIEW Academy, Kottayam, Kerala

ABSTRACT

A system for controlling the speed of a dc motor through internet is proposed. A remote user can visualize and control the motor speed. The control algorithm is designed with the help of fuzzy logic tool box in LabVIEW. Conventional control system design depends upon the development of a mathematical description of the systems behavior. The need to describe mathematically, ever increasing complexity becomes difficult and perhaps infeasible. There may be many difficulties and errors may occur when the motor is controlled without visualizing the motor speed control unit to view the control status. The proposed system uses fuzzy logic tool box in LabVIEW which may eliminates the problems in conventional method of design. An additional PID control options are provided along with fuzzy logic controller so that the user can evaluate the two controller performances and study them. A NI image acquisition tool box and a CCD camera is used for seeing the motor speed control unit to the remote  user to view the control status as such. This continuous camera output is integrated along with a  LabVIEW control panel.

FAULT DETECTION IN LEVEL MEASUREMENT SYSTEM- USING LABVIEW

Brijesh Varghese*, Ebin Alias.K.Varghese*, Jasmine George*, Tony Philip*
Department of Applied Electronics &Instrumentation, SAINTGITS
Under the guidance of: Prof. P.S. Godwin Anand
Project carried out at: SAINTGITS LabVIEW Academy, Kottayam, Kerala

ABSTRACT

Monitoring is a continuous real-time task of determining the conditions of a physical system, by recording information, recognizing and indicating anomalies in the behavior. In other words, the purpose of the monitoring is to indicate whether a process has deviated from its acceptable state, and if it has, why. The deviations are called process faults. Observation of the faults is known as fault detection, which is followed by fault isolation, determination of the location and the type of the fault. Fault Detection and Isolation (FDI) - also known by a common name fault diagnosis - can be carried out in many ways. Fault detection takes as input the current values of the process measurements and produces one or more fault indicator signals, which are often called residuals. After the detection phase there is an inference mechanism which takes the fault indicator(s) as input and decides whether a fault has occurred or not. Detection of a fault is followed by an isolation phase which carries out identification of the fault.   To carry out effective detection, it is first of all necessary to define an event carrying the fault information, which will be an indicator of fault. This event constitutes the Information Signal IS. And to take effectively this fault into account, the knowledge of its arrival moment or fault moment is necessary to proceed either to compensation by adaptation or a correction. There are five principal phases constituting the fault detection,
namely:

1. To establish the hypothesis test
2. To generate the signal information IS,
3. To detect the fault moment,
4. To estimate the fault amplitude,
5. To compensate the fault.