Overview Passive Components, Sources, Krichoffs Law, Modeling of Circuit
39 Lessons
38:48:16 Hours
Overview Contents: Discrete Time Signal and System - Frequency Domain Representation of Discrete Signals - Z-Transform - Solution of Difference Equation
34 Lessons
31:33:57 Hours
Overview Introduction to Vector - Coulomb's Law - Electric Field - Electro Static Potential - The Gradient - Gauss's Law - Poisson's Equation - Energy in the Field
42 Lessons
40:40:44 Hours
Overview Fundamentals Of Energy, Fossil Fuels, Energy Economics, Thermal Power Plants, Hydroelectric Power, Nuclear Fusion Reactors, Solar Thermal Energy Conversion, Photovoltaic Power Generation, Wind Energy, Tidal Energy, Geothermal Energy, Magnetohydrodynamic Power Generation.
40 Lessons
36:43:05 Hours
Overview Introduction, Eye and Vision, Laws of Illumination, Photometry, Incandescent Lamps, Discharge Lamps, Illumination Systems, Glare, color, Interior Lighting, Lighting Calculations and Applications.
20 Lessons
17:43:57 Hours
Overview Contents: Introduction - Architecture of Industrial Automation Systems - Measurement Systems Characteristics - Temperature Measurement - Pressure, Force and Torque Sensors - Motion Sensing - Flow Measurement - Signal Conditioning - Data Acquisition Systems - Introduction to Automatic Control - PID Control-PID Control Tuning - Feedforward Control Ratio Control - Time Delay Systems and Inverse Response Systems - Special Control Structures - Concluding Lesson on Process Control
40 Lessons
39:50:23 Hours
Overview Electric Drive, Controlled Rectifier, Power Electronics Improvements, Dc to Dc Converter, Ac to Dc Converter-Design, Dc Motor Speed Control, Inverter - Current Hysteresis Controlled PWM, Induction Motor.
35 Lessons
31:05:21 Hours
Overview Introduction, Strain gauge, Torque Measurement, Thermistor, Thermocouples, LVDT, Flowmeter, pH and Viscosity Measurement, Dissolved Oxygen Sensors, Chromatography
40 Lessons
39:50:24 Hours
Overview Linear Neural networks, Non linear system analysis, Adaptive learning rate, Fuzzy Logic Control, Neural Model of a Robot manipulator, Adaptive neural control, Linear controllers using T-S fuzzy model.
32 Lessons
31:01:59 Hours