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ELCT 891Y: Sensors

ELCT 891Y: Sensors. Dr. Goutam Koley Room 3A12, 777-3469, koley@engr.sc.edu Lecture Hours: Mon & Wed 4.00 PM – 5.15 PM 300 M, B101 Office Hours: By appointment only Other information: To be posted on the website. Course Information.

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ELCT 891Y: Sensors

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  1. ELCT 891Y: Sensors Dr. Goutam Koley Room 3A12, 777-3469, koley@engr.sc.edu Lecture Hours:Mon & Wed 4.00 PM – 5.15 PM 300 M, B101 Office Hours:By appointment only Other information: To be posted on the website

  2. Course Information Objective: To learn principles of modern sensors and actuators (emphasis on micro and nanoscale sensors) Reference book: Handbook of Modern Sensors: Jacob Fraden, Fourth Edition, Springer. ISBN: 978-1-4419-6465-6 Other notes and handouts will be given from time to time, or references posted on the course website

  3. Schedule and Grading Class: January 9 – April 23, 28 lecture days Final Exam Week: April 25 – May 2, 2012 Grading:Midterm: 30 % Final: 30 % Project and presentation 40 % Approximate Grades:A 90 - 100 B+ 85 - 89 B 80 - 84 C+ 75 - 79 C 70 – 74 D+ 65 – 69 D 60 – 64 F <60

  4. Lectures: 18 Classes Midterm: 1 Class Revision: 2 Classes Student Presentations (2 sets): 8 Classes Class schedule A project report has to be submitted by each of the students at the end of the semester on the last day of classes, i.e. on April 23.

  5. Course Contents 1 • Sensor characteristics (1) • Position and Displacement sensors (2) • Positions sensors • Displacement sensors • Level sensors • Velocity and Acceleration sensors (2) • Velocity sensing • Acceleration sensing • Force and Strain sensors (2) • Force sensors • Strain sensors

  6. Course Contents 2 • Pressure and Flow sensors (1) • Pressure sensors • Flow sensors • Acoustic sensor (1) • Humidity sensor (1) • Radiation sensor (1) • Chemical Sensors (3) • Microcantilevers as sensing elements (2) • Basics of microcantilever based sensing • Applications in sensing • Nanoscale sensors and applications (1) • Nanowire based sensors • CNT and Graphene based sensors

  7. List of projects Automotive accelerometer Explosive detection systems Mass flow and pressure sensors/controllers Cooled and Uncooled IR sensors Nanoscale bio-sensors for pathogen detection MEMS gyroscopes for navigation RFID based temperature and humidity sensors Strain sensors for prognostics in airplanes and bridges Volatile organic compound sensors Automotive O2 and NOx sensors MEMS/NEMS sensors for pathogen and toxic gases Project topics

  8. Transfer Function: The functional relationship between physical input signal and electrical output signal. Usually, this relationship is represented as a graph showing the relationship between the input and output signal, and the details of this relationship may constitute a complete description of the sensor characteristics. Examples of Transfer function: Linear: Vout = A + Bs Non-linear: Vout = Beks = B(1+ks+k2s2/2+..) Here s is the input signal and Vout is the electrical output Sensor Characteristics A non-linear transfer function can be linearized using piecewise approximation

  9. Sensor Characteristics Sensitivity: The sensitivity S is defined as the ratio between a small change in electrical signal to a small change in physical signal. As such, it may be expressed as the derivative of the transfer function with respect to physical signal. Mathematically, it is given as: For a linear transfer function such as Vout = A + Bs, the sensitivity would simply be B. For a non-linear transfer function, the sensitivity would vary with the particular segment of the linearization.

  10. Span or Dynamic Range: The range of input physical signals which may be converted to electrical signals by the sensor. Signals outside of this range are expected to cause unacceptably large inaccuracy. This span or dynamic range is usually specified by the sensor supplier as the range over which other performance characteristics described in the sheets are expected to apply. Sensor Characteristics Hysteresis: Some sensors do not return to the same output value when the input stimulus is cycled up or down. The width of the expected error in terms of the measured quantity is defined as the hysteresis. Typical units: % of FSO

  11. Accuracy: Generally defined as the largest expected error between actual and ideal output signals. Sometimes this is quoted as a fraction of the full scale output. Sensor Characteristics

  12. Non-linearity: The maximum deviation from a linear transfer function over the specified dynamic range. There are several measures of this error. The most common compares the actual transfer function with the `best straight line', which lies midway between the two parallel lines which encompasses the entire transfer function over the specified dynamic range of the device. This choice of comparison method is popular because it makes most sensors look the best. Sensor Characteristics

  13. Noise: All sensors produce some output noise in addition to the output signal. In some cases, the noise of the sensor is less than the noise of the next element in the electronics, or less than the fluctuations in the physical signal, in which case it is not important. Noise is generally distributed across the frequency spectrum. Many common noise sources produce a white noise distribution, which is to say that the spectral noise density is the same at all frequencies. Johnson noise in a resistor is a good example of such a noise distribution. For white noise, the spectral noise density is characterized in units of Volts/(Hz). A distribution of this nature adds noise to a measurement with amplitude proportional to the  (Measurement bandwidth B). Since there is an inverse relationship between the bandwidth and measurement time, it can be said that the noise decreases with the square root of the measurement time. Sensor Characteristics

  14. Resolution: The resolution of a sensor is defined as the minimum detectable signal fluctuation. Many sensors are limited by noise with a white spectral distribution. In these cases, the resolution may be specified in units of (physical signal)/(Hz). Sensor data sheets generally quote resolution in units of signal/(Hz) or they give a minimum detectable signal for a specific measurement. The actual resolution for a particular measurement may be obtained by multiplying this quantity by the square root of the measurement bandwidth. Thus, the lower the bandwidth, the higher is the resolution. Bandwidth: All sensors have finite response times to an instantaneous change in physical signal. In addition, many sensors have decay times, which would represent the time after a step change in physical signal for the sensor output to decay to its original value. The reciprocal of these times correspond to the upper and lower cutoff frequencies, respectively. The bandwidth of a sensor is the frequency range between these two frequencies. Sensor Characteristics

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