Artificial Intelligence Applications in Engineering (MUH-920), week 9 of 14: interactive lab
Prof. Dr. Utku Kose, Süleyman Demirel University
Part A places points by clicking and compares k-means with DBSCAN on the same data, with controls for k, eps and the minimum number of neighbours [1]. Part B synthesises the vibration of a bearing with adjustable shaft speed, fault severity and noise, and shows the waveform, the spectrum and the envelope spectrum with the computed fault frequency, together with RMS, kurtosis and crest factor [2].
Click on either panel to add points.
Six questions with instant feedback. Rate your confidence before checking each answer.
Answers are saved in this browser only. The export creates a Markdown learning log for your portfolio.
After the export, continue with the discipline challenge and the weekly task in the week overview.
[1] Ester, M., Kriegel, H.-P., Sander, J., & Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96) (pp. 226-231). AAAI Press.
[2] Randall, R. B., & Antoni, J. (2011). Rolling element bearing diagnostics: A tutorial. Mechanical Systems and Signal Processing, 25(2), 485-520. https://doi.org/10.1016/j.ymssp.2010.07.017
[3] Lloyd, S. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. https://doi.org/10.1109/TIT.1982.1056489
[4] Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202