ENME351: Electronics and Instrumentation II

In this course, the student will develop and/or refine the following areas of knowledge:

• Quantitatively evaluate an instrument on the basis of metrics, such as accuracy and hysteresis, and instrument error specifications.
• Understand how to appropriately apply controls, blocking, and randomization to collect meaningful data.
• Be able to use, generate, and describe the purpose of a calibration curve.
• Be able to describe, mathematically and graphically, the behavior of zero, first, and second order system to step and sinusoidal inputs. Be able to extract characteristic parameters, such as the time constant, from plots and mathematical expressions of the response to such inputs and apply those parameters to predict the response of the system to other inputs.
• Know how to perform a Fourier analysis, both graphically and mathematically. Be able to predict the amplitude versus time curve from a simple frequency spectrum and vice versa. Be able to apply basic Fourier transform principles to the construction of a periodic function from a sum of sine waves.
• Be able to apply an appropriate filter to a signal to remove noise without distorting the signal.
• Be able to use an appropriate sampling rate that does not produce aliasing and that does so with a minimum file size. Be able to predict the alias frequency and phase of a signal based on parameters such as the sampling rate. Be able to explain the aliasing effect mathematically and graphically.
• Understand how to find the output of simple op-amp circuits with feedback. Understand the output of an op-amp without feedback.
• Understand how analog to digital and digital to analog converters work, at the circuit level, and evaluate their performance based on specifications such as clock speed and number of digits. Be able to articulate the trade-offs in the main four types of analog to digital converters.
• Be able to write simple programs in LabVIEW, a graphical programming language for the creation of virtual instruments.
• Recognize that there is a problem with the data when it is distorted, aliased, etc. and know how to change instrument settings to fix the problem.
• Be able to estimate mean, standard deviation, drift, signal to noise ratio, and other statistics and metrics from looking at data plots.
• Be able to calculate the best estimate of a measurement’s error based on instrument specifications and experimental uncertainties. Understand the origin and nature of these uncertainties.
• Understand some of the basic physics underlying solid state devices: electrons and holes in semiconductors, band gaps, p-n junctions, band tilting under an electric field.
• Be able to take good laboratory notes and write a report from those notes. Be able to articulate what experiments were performed and for what purpose, describe what happened in the experiment, using text, tables, figures, and plots, and explain the significance of what happened. Be able to thoughtfully examine the data from the laboratory experiments and draw conclusions.
• Use bridge circuits in the laboratory, be able to design an appropriate bridge circuit for a given measurement, and be able to give the output of the circuit to a change in the sensor resistance.
• Be able to measure temperature with a thermocouple. Understand the thermocouple time constant in air versus water. Be able to reduce noise in the signal using Labview.
• Understand and explain, in words and mathematically, the similarity of mass-spring systems and the mechanical behavior of beams. Explain the similarities between a first order thermocouple system and a first order RC circuit. Be able to obtain the spring constant (Young’s modulus) from static and dynamic measurements if the mass is known, or vice versa.
• Be able to apply statistics concepts and calculations to real data.

• Digital logic and logic circuits
• Arduino hardware and programming
• ADCs, sampling, and aliasing
• Frequency domain and Fourier analysis
• 1st and 2nd order sensor dynamics
• Amplification
• Noise and filters
• Strain sensing
• Sensing error and calibration
• DACs
• Actuation, DC motors, stepper motors, and motor control