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Viewing: CE 557 : Engineering Measurement and Data Analysis

Last approved: Tue, 16 Jan 2018 21:15:58 GMT

Last edit: Tue, 16 Jan 2018 21:15:49 GMT

Change Type
Major
CE (Civil Engineering)
557
002926
Dual-Level Course
No
Cross-listed Course
No
Engineering Measurement and Data Analysis
Engr. Meas. and Data Analysis
College of Engineering
Civil Engineering (14CE)
Term Offering
Fall Only
Offered Every Year
Fall 2018
Previously taught as Special Topics?
Yes
5
 
Course Prefix/NumberSemester/Term OfferedEnrollment
CE596F20137
CE596F20148
CE596F20157
CE596F20169
CE596F20178
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded/Audit
3
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture2
Laboratory2
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Andrew Grieshop
Assistant Professor
full

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture and Lab1212NoOne limitation to enrollment has been that course is listed as a 'Environmental Engineering Special Topics' Course, even though material is not specific to environmental engineering. I anticipate having a course number may help with this confusion.
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote


Is the course required or an elective for a Curriculum?
No
The course will introduce students to fundamentals of experimental design, measurement systems and applied data analysis techniques and includes 'hands-on' laboratory exercises with sensors and computer-based data acquisition. Emphasis is on general concepts and their practical application towards engineering problems. The goal of the class is to build needed background, skills and vocabulary to develop students' experimental practice rather than focusing on the underlying fundamentals of distinct areas. Students will develop more topic/media-specific knowledge through a team experimental project. Prerequisites include a course in statistics (e.g. ST 370, ST 515 or equivalent) and some coursework or experience involving scientific programming (e.g. CE 536 or 537; Matlab, Python, R, Igor Pro, IDL). Appropriate background can be determined via discussion with instructor.

Sensors and computer-based data acquisition have become ubiquitous in all engineering research, yet incoming graduate students in Civil and Environmental Engineering  do not necessarily get exposed to such systems during undergraduate lab experiences. Likewise, students often have limited exposure to good practices in analysis and graphical presentation of measurement data from such systems. This course aims to equip students in these programs with tools and background that can be applied in all engineering measurement applications, regardless of the specific area or media (e.g. environmental media, engineering materials, geotechnical engineering) of their research or professional plans. The special topics course has been taken by Civil and Environmental Engineering students, as well as several students from Marine Earth and Atmospheric Sciences. 


No

Is this a GEP Course?
GEP Categories

Humanities Open when gep_category = HUM
Each course in the Humanities category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

College(s)Contact NameStatement Summary
College of EngineeringI did not consult with any other departments in this process, as I could not find any courses with substantial overlap at the proper level. The closest overlap is probably with the undergraduate measurement laboratory sequence in Mechanical Engineering (MAE 305/306), but since it is undergraduate and has a number of MAE prerequisites, it is not an option for the Civil and Environmental Engineering graduate students that are the target for this course.
The instructor has been teaching this each Fall for the past 5 years. Additional resources required (e.g. lab space, data acquisition equipment, sensors) have been acquired during this development, so no new instructional resources are required.

The objective of this course is to give students the background knowledge and tools to get inside the ‘black box’ of measurements and sensors to ensure that proper instruments and appropriate analyses are selected. Essentially all measurements now involve sensors and computer interfaces of one kind or another. Therefore, an understanding of the workings of measurement systems is crucial in using, designing or specifying a monitoring or experimental system. Further, the design of measurements and the analysis of the resulting data are fundamentally linked: a measurement system’s capabilities must be considered in analysis, and the type of analysis required often drives the selection of measurements.The course will introduce students to fundamentals of experimental design, measurement systems and applied data analysis techniques and includes ‘hands-on’ laboratory exercises with sensors and computer-based data acquisition.  See 'Student Learning Outcomes' for specific educational goals. 


Student Learning Outcomes

 By the end of the course, students will be able to:


1) Conduct elementary DC circuit analysis with Kirchhoff’s laws and equivalence in RLC circuit components and build simple DC circuits on breadboards.


2) Explain component impedance matching and the operation of different sensor/transducer and signal conditioning systems 


3) Quantify and evaluate the time response of first-order systems. 


4) Identify appropriate sampling configuration for measurement systems and identify resolution and associated uncertainty. 


5) Classify time varying signals and plot their amplitude and power spectra and determine proper sampling frequencies for discrete data


6) Describe aliasing and amplitude ambiguity and determine the appropriate sample period and rate, filtering and instrument signal ranges for use in a PC-based data acquisition system.  


7) Conduct error analysis of measurements and distinguish between systematic and random errors, estimate design-stage and measurement uncertainties.


8) Implement automated data analysis using scripting software.


9) Conduct least squares regressions and correlation analyses on data and calculate confidence intervals on fits and auto-correlation in time-series data.


Evaluation MethodWeighting/Points for EachDetails
Participation10Class and lab preparatory activities (reading questions), lab notebook status
Written Assignment20Lab reports and homework assignments
Exam15Midterm Exam
Final Exam25Take-home Exam
Major Paper30Team experimental project - proposals, report and presentation
TopicTime Devoted to Each TopicActivity
Introduction2 classesCourse introduction; Introduction to measurement and uncertainty
Circuit analysis 3 classesIntroduction/review of basic DC circuit components and analysis
Measurement systems5 classesSensors and measurement systems, sensor response characterization, signal amplification and passive filtering, analog to digital conversion
Uncertainty analysis3 classesIntroduction to uncertainty analysis, Taylor series uncertainty propagation, design stage uncertainty analysis,
Least squares regression and correlation4 classesLinear least squares regression, data transforms for linear fitting, uncertainty in least squares fits
Calibration and system response3 classesCalibration and response of zero- and first-order systems to step and sinusoidal forcing
Digital sampling and the time and frequency domain4 classesIntroduction to the time and frequency domain, signal characteristics and sampling design (Nyquist frequency, aliasing), Signal processing (discrete and fast Fourier transforms)
Graphical presentation of data2 classesEffective graphical communication of data, formatting and communication of data and analysis in written and oral formats.
Student project workshops and presentations3 classesProject brainstorming and team formation, end of semester presentations of team projects.
Suggested course number was discussed with Environmental, Water Resources and Coastal Engineering Faculty and reflects the 'cross-group' (e.g. not specific to any of the topic areas within the graduate program) nature of the course.

A challenge in developing the course has been finding suitable time slots to meet the contact hour requirements. I have developed the course as a 2 hour lecture/2 hour lab offering, but haven't had a way to 'officially' schedule the course in these time slots - I have either used 2 of 3 50-minute class periods (e.g. MW for a MWF lecture) or 60 minutes of 75 minute periods. I will need help figuring out how to appropriately schedule the course in the future.

mlnosbis 11/10/2017:
1) Effective date should be Spring 2018 or later; it is too late for Fall 2017
2) The statement in the prerequisite field cannot be coded in the schedule. If there are specific course prerequisites, you can list them here, otherwise this statement should be moved to the end of the course descriptions so students can see it in the catalog. We can code permission of instructor and then you can add the rest of the statement to the end of the description.
3) Given your note on the syllabus about the course being 1 hour with a 2 hour lab, I don't think that this is a 3-credit course. https://oucc.dasa.ncsu.edu/courseleaf-2/instructional-formats/. OK
4) Syllabus notes:
- Include price of textbook
- The items listed as course objectives should be identified as Student Learning Outcomes and match the CIM form. Objectives/goals are broad goals for the course. You can include the statement from the Course Objectives/Goals field of the CIM form on the syllabus and identify that as goals.
- Include instructors policies on attendance and late assignments. See the Graduate Syllabus Checklist attached under additional documentation.

pjharrie - 11/15/17 - no comments beyond Melissa's beyond two things: it's unclear based on what's in CIM and what's in the syllabus, whether there are one or two hours of lecture and how will the teams be chosen and what will determine whether they are 2 or 3 students (would a 2-person team be at a disadvantage or would that only happen if you have an odd number of students in the course?)

Andy Grieshop 11/29/2017 - I think I have addressed all of the issues noted here. Some confusing wording in the syllabus has hopefully been cleared up (there are two one-hour lectures and one two-hour labs for the course) and details on the requested items (e.g. attendance/lateness policies, textbook price) have been added. I have removed coded prerequisites and have added that material to course description.

ABGS Reviewer Comments (12/4/2017):
-No Comments.
sarumug (Sat, 04 Feb 2017 09:59:53 GMT): Rollback: Andy,Work with Cassie in revising the course action form.
ranji (Fri, 10 Mar 2017 18:50:08 GMT): Update the number of offerings in the past 5 years to 4
ranji (Fri, 10 Mar 2017 18:59:45 GMT): For Course Description, state what the course is and avid listing what it is not.
ranji (Fri, 10 Mar 2017 19:00:50 GMT): Course Objective is verbose; could be more succinct
sarumug (Fri, 10 Mar 2017 19:01:09 GMT): Pre-requisite better to be precise: CE 370 and a computing course CE 339. Most of the courses listed there are 500-level classes.
sarumug (Fri, 10 Mar 2017 19:04:23 GMT): Rollback: In the syllabus, the lecture portion says only 1 hour, whereas the course action form says 2 contact hours for lectures. Try to be consistent on both.
sarumug (Fri, 10 Mar 2017 21:28:27 GMT): Rollback: Please address the comments that I shared with you from the GPC.
sarumug (Mon, 17 Apr 2017 16:50:52 GMT): Rollback: Pushing it back to include the revised syllabus.
sarumug (Fri, 28 Apr 2017 18:15:07 GMT): Rollback: Please revise.
ranji (Mon, 07 Aug 2017 10:46:25 GMT): Wait for approval from the CE course scheduling officer.
mlnosbis (Mon, 13 Nov 2017 14:32:20 GMT): Note from Doug Reeves: The course content overlaps substantially with multiple ECE undergraduate courses, but is more accessible to CCEE graduate students than taking those courses, and is a more pragmatic, hands-on view of the topics. The instructor may find it useful at some point to discuss his course with some of those faculty. Otherwise, no changes requested.
Key: 9942