Spectrum Analysis
Owner: Prof Martin Fullekrug
Number of students: 2
Formative Deadline: Friday W8
Learning Outcomes
Spectral analysis is an important skill for Engineers to detect signals in time series, to quantify the amplitudes of signals at specific frequencies, and to determine the frequency content of signals. Mastering this skill requires expertise in spectral analysis and its numerical implementation. The main result of spectral analysis is the calculation of a spectrum which shows how the amplitudes of a signal depend on frequency, known as the spectral content.
Knowledge Requirements
To claim this skill, the page includes a username, characterisation of a time series, and a figure of a spectrum, along with a descriptive figure caption stating 1.1-1.4.
- The characterisation of the time series includes the 1.1 sampling time interval 1.2 number of samples in the recordings 1.3 total time of the recordings 1.4 fundamental frequency of the recordings
- Screenshot of spectrum of a signal used in the lab includes a 2.1 frequency axis 2.2 amplitude axis 2.3 spectrum of the signal
Application Requirements
To claim this skill, the page includes a username, characterisation of a real-world time series, and a figure of its spectrum, along with a descriptive figure caption ~50-100 words.
- The characterisation of the time series includes the 1.1 sampling time interval 1.2 number of samples in the recordings 1.3 total time of the recordings 1.4 fundamental frequency of the recordings
- The screenshot of the spectrum a real-world signal used in the lab includes a 2.1 frequency axis labelled with the unit of frequency used 2.2 amplitude axis labelled with the unit of amplitude used 2.3 spectrum of a real-world signal
- The figure caption includes the 3.1 dominant frequency of the spectrum shown in the figure 3.2 amplitude of the dominant frequency shown in the figure
Synthesis Requirements
To claim this skill, the page includes a username, characterisation of a time series, and a figure of a spectrum, along with a descriptive figure caption ~50-100 words.
- The characterisation of the time series includes the 1.1 sampling time interval 1.2 number of samples in the recordings 1.3 total time of the recordings 1.4 fundamental frequency of the recordings
- The screenshot of the spectrum includes a 2.1 frequency axis labelled with the unit of frequency used 2.2 amplitude axis labelled with the unit of amplitude used 2.3 spectrum of a signal from an independent project
- The figure caption includes the 3.1 dominant frequency of the spectrum shown in the figure 3.2 amplitude of the dominant frequency shown in the figure 3.3 main conclusion from what is shown in the spectrum in the context of the application in the independent project
Knowledge Opportunities
Lab W7
Application Opportunities
Lab W7