Difference between revisions of "Instrumentation"
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This course is taught in the third year of the electrical engineering curriculum. The course mainly deals with transducers for non-electrical quantities and their application to measurement of primary variables. Other areas covered in this course include signal conditioning, remote sensing techniques, microprocessor applications in instrumentation, noise and interference reduction, data storage, recording and display systems. | This course is taught in the third year of the electrical engineering curriculum. The course mainly deals with transducers for non-electrical quantities and their application to measurement of primary variables. Other areas covered in this course include signal conditioning, remote sensing techniques, microprocessor applications in instrumentation, noise and interference reduction, data storage, recording and display systems. | ||
| − | We | + | We aim to develop a laboratory exercise that will introduce the students to signal conditioning and remote sensing. Remote sensing is important in instrumentation as it enables collection of data from measurement points at inconvenient locations. |
In this lab, the students will use a strain gauge to measure forces and transmit data to a different location via a wireless module. The Raspberry Pi will receive the data, perform signal conditioning and display the measurements. | In this lab, the students will use a strain gauge to measure forces and transmit data to a different location via a wireless module. The Raspberry Pi will receive the data, perform signal conditioning and display the measurements. | ||
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| + | Two labs are under development as follows | ||
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| + | #Analog to Digital Conversion | ||
Revision as of 19:43, 13 July 2015
Instrumentation
This course is taught in the third year of the electrical engineering curriculum. The course mainly deals with transducers for non-electrical quantities and their application to measurement of primary variables. Other areas covered in this course include signal conditioning, remote sensing techniques, microprocessor applications in instrumentation, noise and interference reduction, data storage, recording and display systems.
We aim to develop a laboratory exercise that will introduce the students to signal conditioning and remote sensing. Remote sensing is important in instrumentation as it enables collection of data from measurement points at inconvenient locations.
In this lab, the students will use a strain gauge to measure forces and transmit data to a different location via a wireless module. The Raspberry Pi will receive the data, perform signal conditioning and display the measurements.
Two labs are under development as follows
- Analog to Digital Conversion
