ECE 446

• Core Curriculum

Students will learn to use LabView, Origin, and Matlab through several assignments.

Students will build and test: (1) a software based lock-in amplifier in LabVIEW using a DAQ card, (2) a PID motor controller in LabVIEW using table top instruments, (3) audio and optical heterodyne systems, and (4) an electrical time domain reflectometer. They will also carry out an experimental project of their own design that determines and models the main effects and their statistical significance in a multivariable experiment.

Probability and statistics from ECE 313

1. Principles of Experimental Research Course Packet, F&S Printing Department, 2017.
2. Data Reduction and Error Analysis for the Physical Sciences by Philip R. Bevington and D. Keith Robinson (publisher: McGraw-Hill), 3^rd edition, 2003.
3. NIST/SEMATECH e-Handbook of Statistical Methods, available free of charge online at: http://www.itl.nist.gov/div898/handbook/

Selected Elective

Engineering Science: 100%

This course is designed primarily for first year engineering and science graduate students and advanced undergraduates interested in pursuing a career or an advanced degree involving experimental research. The overarching course goal is for students to understand a wide variety of experimental methods and to be able to directly apply them in the lab.

By the first quiz, the students should be able to do the following:

• Plan an experimental research project (1, 2, 5, 6)
• Perform basic LabView programming (1, 6, 7)
• Use null and differential techniques for high precision high accuracy measurements (1, 6, 7)
• Explain the operating principles of a lock-in amplifier (1, 2, 6, 7)
• Select appropriate grounding configurations for low noise measurements (1, 6, 7)
• Understand static and dynamic characteristics listed on an instrument spec sheet (1, 6, 7)
• Identify common sources of measurement error and suggest techniques to improve the precision and accuracy of measurements (1, 6, 7)
• Perform error propagation (1, 6, 7)
• Use back of the envelope calculations to assess the feasibility of a proposed idea (1, 6, 7)
• Use dimensional analysis to reduce the number of variables describing the underlying physical equations (1, 6, 7)
• Use a PID control loop to stabilize a system (1, 2, 5, 6, 7)
• Use DOE to select an appropriate design and to choose sample testing points in order to meet stated experimental objectives (1, 6, 7)

By the second quiz, the students should also be able to do the following:

• Design fractional factorial experiments and also determine the generators, defining relation, aliasing structure, and resolution of a given design (1, 6, 7)
• Perform initial analyses of DOE data (1, 6, 7)
• Perform linear, multivariate linear, single variable polynomial regression and robust linear fitting and interpret the results of such calculations (1, 6, 7)
• Define sensitivity and specificity and determine the probability of type I and type II errors (1, 6, 7)
• Formulate and test a hypothesis for significance using the t-test, χ²-test, or F-test (1, 6, 7)
• Define confidence intervals (1, 6, 7)
• Draw the ROC curve for a binary classifier and determine a suitable operation point (1, 6, 7)
• Use ANOVA and the F-test to determine whether a factor is statistically significant (1, 6, 7)
• Interpret ANOVA data from a least squares regression (1, 6, 7)
• Analyze DOE data for full and fractional factorial experiments to determine the statistically significant factors and interactions (1, 6, 7)
• Prepare sketches for machining or rapid prototyping using proper dimensioning and discuss choices for the tool and material to be used (1, 2)

By the end of the course, the students also should be able to do the following:

• Prepare experimental results for conference presentation or journal publication using IEEE style guidelines (3,4)
• Perform nonlinear curve fitting (1, 6, 7)
• Understand their ethical responsibilities as a researcher (4)
• Evaluate the goodness of a fit (1, 6, 7)
• Setup cross validation training and test sets (1, 6, 7)
• Interpolate and extrapolate data (1, 6, 7)
• Perform numerical integration and differentiation (1, 6, 7)
• Use noise filtering, smoothing, and averaging techniques to analyze noisy data and to find critical points (1, 6, 7)
• Use self-calibration and/or heterodyne techniques for high precision high accuracy measurements (1, 6, 7)
• Use Monte Carlo techniques to experiment via simulation and to estimate the uncertainty in parameters through the method of bootstrapping (1, 6, 7)
• Evaluate the progress of a project in terms of schedule and cost and forecast the project cost at completion and the estimated date for completion (2)
• Use principle component analysis to reduce multidimensional data sets to lower dimensions for detailed analysis (1, 6, 7)
• Summarize a proposed experimental technique in basic terms, explain the problem the technique addresses, and analyze the assumptions, advantages, disadvantages, and limitations of the technique. Specific techniques to be known are: pump probe experiments, time domain reflectometry, temperature dependent studies, wavelength modulation spectroscopy, and cavity ringdown spectroscopy. (1, 2, 3, 5, 6, 7)