The primary course objectives are 1) to understand how to design instrumentation for static and dynamic testing and 2) how to interpret physical data using a variety of signal processing tools. The course will cover the basic theory and implementation of various sensor technologies, including strain gages, accelerometers, and digital image correlation. Digital signal processing concepts such as sampling, filtering, noise, and correlation will be covered in detail, both in the time and frequency domains. Applications in Structural Health Monitoring of civil infrastructure will be discussed. This course will also make extensive use of experimental data from students' research and in-class demonstrations.

• Conduct experiments using a variety of available measurement technology by understanding mounting, amplification and conditioning requirements.
• Understand and apply fundamental frequency domain concepts like sampling, aliasing, filtering, fourier transforms, and power spectral density.
• Understand and apply fundamental time domain concepts like correlation, variance, power and additional statistical properties of signals.
• Gain experience with real data.

• Rodrigo Sarlo