Master Course Syllabus for EE 484 (ABET sheet)
Title: SENSORS AND SENSOR SYSTEMS
Coordinator: Denise Wilson, Associate Professor, Electrical Engineering
Goals: This capstone design course provides seniors with a chosen area of concentration or interest in sensors and devices with skills in the open-ended design of sensor systems.
Objectives: At the end of this course, students will be able to
1. Formulate and solve open-ended design problems in the systems of sensors and related devices including electronic interface circuits.
2. Write formal project reports.
3. Make formal project presentations.
4. Work in teams with heterogeneous knowledge and skills.
5. Apply governing mechanisms of particular sensor technologies, basic transduction mechanisms, noise properties, sources of environmental interference, and computer simulation to the design of complete sensor systems whose overall performance is defined and demonstrated using standardized system metrics.
6. Demonstrate an awareness of benefits and drawbacks of predominant sensor technologies.
Textbook: Class notes, textbook excerpts, and journal articles.
1. Mike MarkelWriting in the Technical Fields, IEEE Publications
2. Kellie Cook, "Layered Literacies: A Theoretical Frame for Technical Communication Pedagogy," Tech Communication Quarterly, Winter 2002, pp. 5-29.
3. Cliff Atkinson, Beyond Bullet Points, Microsoft Press: 2005.
Prerequisites: EE331 or Instructor Permission
Prerequisites by Topic:
1. Fundamental circuit analysis
2. Discrete electronic circuit design
3. Computer literacy with Matlab, word processing, presentation and spreadsheet software
4. Novice capability in Labview and Data Acquisition
5. Fluency in basic electronic test equipment usage
1. Introduction - 1 week
2. Sensor Performance Metrics - 0.5 weeks
3. Review of mechanical, biochemical, radiant, and thermal sensors - 3 weeks
4. Engineering Design, Design of Experiments, and Statistical Analysis of Experimental Data: 2.5 weeks
5. Project Reports, Presentations, and Design Project Feedback - 3 weeks
Course Structure: The class typically meets for two lectures a week, each consisting of two 80-minute sessions. Approximately half of sessions are organized into short lectures on technical topics (sensors) or engineering design topics. The other half of sessions are committed to design project group activity, including presentations, feedback, and working design sessions. The design project begins at the start of the quarter with a project proposal followed by regularly spaced milestones throughout the quarter (Proposal; System Design; System Analysis and Simulation; Proof of Concept Results; System Characterization; Performance Figures of Merit; and Final Report). A written and oral project report from each team is due at the end of the course.There are no exams; however, many collaborative learning sessions and in-class design project group presentations will be graded.
Computer and Laboratory Resources: Design projects require a combination of standard software packages (Matlab, Labview, Microsoft Excel/Word/Powerpoint) and test equipment resources (National Instruments Data Acquisition cards and standard EE1 139 multimeters, power supply, and oscilloscopes).
Grading: In-class exercises and short concept quizzes 30% of the grade; and the design project 70% of the grade.
Outcome Coverage: This course provides the ABET major design experience and addresses several basic ABET outcomes.
Outcomes: High, Medium, Low indicates level of coverage
(a, Medium) An ability to apply knowledge of mathematics, science, and engineering. The design of sensor systems requires basic (science) understanding of the governing mechanisms of both sensor and transduction techniques. The interaction between sensor and transduction must also be understood mathematically (including noise analysis). Design and implementation of appropriate signal processing circuits (both analog and digital) to sensor system design involves significant application of engineering principles and design process. The final sensor system must meet specified and useful (standardized) performance metrics. Demonstration of these metrics through appropriate testing protocols shows the student's achievement of this outcome.
(b, High) an ability to design and conduct experiments, as well as to analyze and interpret data. The design project requires that students benchmark performance metrics of their sensor systems against commercial systems to establish their usefulness in the designated market. Experiments must be designed to show, statistically, that sensor design remains within acceptable limits of the benchmark.
(c, High) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability. Sensor systems, in many cases, inherently aim to improve the environmental, health, safety, manufacturability, or social impact of a larger system. Students consider and implement the sensor system design in the context of improving a targeted societal impact. For example, students may design a low-cost temperature control module for solder reflow systems that improves overall manufacturability (cost, reliability) of printed circuit boards in small batch/company applications. Implications of small batch solder reflow instruments to environmental sustainability might also be considered in such a project.
(d, High) an ability to function on multi-disciplinary teams. Students will operate in teams of 3-4 to design the sensor system in a community of learners format. Students offer heterogeneous expertise to the system design that evolves as a function of natural interest in particular aspects of the design over others. Students are allowed as much flexibility in assigning team function as possible within the constraints of completing a successful demonstration of their designs. Some students may focus on testing, others on statistical characterization of system performance, others on circuit design, others on sensor/transduction behavior derivation, and so on.
(e, Medium) an ability to identify, formulate, and solve engineering problems. The sensor system design problem presents itself as a series of interconnected engineering problems. In the open-ended design environment, the engineering problems are not explicitly stated, but must be identified by the design team before they can be solved. Evidence of this should appear in the project report and progress reports.
(f, Medium) an understanding of professional and ethical responsibility. Students are asked to assess difficult situations in the K-12 classroom (observed through service learning activities) in the context of their society's code of ethics (typically IEEE). Broader ethical examples (space shuttle) are used to develop and define realistic strategies for adhering to ethical codes in individual choices in the work environment.
(g, High) an ability to communicate effectively. Teams must prepare an extensive written project report, and make an oral presentation at the end of the class. Team contributions to the final report are submitted individually and as a final paper product. Teams must demonstrate the "Beyond Bullets"/storytelling approach in their final oral presentation. Effectiveness of the storytelling approach will be evaluated via a peer marketability survey of each sensor system. Final reports will be graded based on all of the layered technical writing literacies outlined by Cook for effective and convincing technical writing.
(k, High) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. Students are expected to use mainstream math processing, data acquisition, and data presentation software to design, analyze, characterize, and summarize sensor system performance. Students must also use general purpose test equipment and electronic interface circuits to extract system performance from their designs. Evidence of the use of these tools, and associated techniques, appears in the project report.
(l, High) knowledge of probability and statistics, including applications appropriate to electrical engineering . This course centers on the design of sensor systems that involve the conversion of multiple forms of energy to electronic form; transient and steady-state behavior of these systems are extracted using first-order governing mechanisms of sensors, transduction mechanisms, interface circuits, and signal processing.
(n, High) Knowledge of mathematics through differential and integral calculus, basic sciences, computer science, and engineering sciences necessary to analyze and design complex electrical and electronic devices, software, and systems containing hardware and software components, as appropriate to program objectives.
ABET Criterion 4 Considerations
Engineering standards - Students are provided with standardized sensor system performance metrics (resolution, sensitivity, etc.) that must be benchmarked against a comparable commercial system to argue viability and usefulness of the student design.
Realistic constraints - The sensor system design chosen and demonstrated by each student team must demonstrate performance metrics competitive with an appropriate benchmark, achieve a footprint acceptable for designated application (benchtop, portable, handheld), and project errors (false positives, false negatives, etc.) deemed acceptable by the end user (as extrapolated from the existing literature for a particular sensing problem).
Preparer: D.M. Wilson
Last revised: 01/10/13