31.4. Data Acquisition and Processing Techniques

Try these first

1. 1.

   What does FFT stand for?

   Hint

   Think about transforming signals.

2. 2.

   Name one technique of supervised learning.

   Hint

   These techniques use past outcomes to predict future ones.

3. 3.

   What is the primary benefit of using FFT in predictive maintenance?

   • To convert time-domain data to frequency-domain.
   • To cluster data points.
   • To enhance image recognition.

   Hint

   Think about the type of signal processing involved.

4. 4.

   True or False: Unsupervised learning requires labeled data.

   • True
   • False

   Hint

   Consider how data classification is approached.

5. 5.

   Design a predictive maintenance strategy using both supervised and unsupervised learning. What types of data would each technique prioritize?

   Hint

   Consider the datasets available to you.

6. 6.

   Evaluate a scenario where poor signal processing could directly impact predictive maintenance outcomes. What steps would you recommend to mitigate this?

   Hint

   Think about the implications of data integrity.