Descriptive Statistics of Aircraft Engines Sensor Data
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Questions and Answers

Why are sensors with a standard deviation of 0 considered not relevant for the remaining useful life prediction?

These sensors are always constant.

What does a positive skewness value indicate in the distribution of temperature sensor T50?

More high-value outliers.

Why is investigating outliers important in RUL prediction?

Outliers can be due to system faults close to the end of the lifetime.

How can you describe the distribution of temperature sensor P30?

<p>Approximately normally distributed, but skewed with more low-value outliers.</p> Signup and view all the answers

What does it mean when mean and median are not equal in data distributions?

<p>The data distribution is skewed.</p> Signup and view all the answers

What is the difference between structured and unstructured data?

<p>Structured data is highly organized and can be stored in a relational database or csv-file, while unstructured data has no organizational form and can be in the form of text or image files.</p> Signup and view all the answers

What is the main focus of Natural Language Processing?

<p>The main focus of Natural Language Processing is processing and analyzing text-based data.</p> Signup and view all the answers

Where does technical data come from?

<p>Technical data comes from a wide variety of sources such as websites, product flyers, and other documentation.</p> Signup and view all the answers

Give an example of a source for technical data.

<p>One example of a source for technical data is the Arduino Uno Rev3 from the Arduino store.</p> Signup and view all the answers

What is the significance of sensors in data acquisition?

<p>Sensors play a crucial role in data acquisition by capturing real-world data and converting it into digital signals for analysis.</p> Signup and view all the answers

What is the main challenge associated with acquiring data using sensors?

<p>Labeling the data is labor-intensive</p> Signup and view all the answers

How does Google reCAPTCHA utilize human effort for data-related tasks?

<p>Human effort is used to digitize text, annotate images, and build machine learning datasets.</p> Signup and view all the answers

What type of data is required for supervised machine learning tasks like predictive quality or predictive maintenance?

<p>Labeled data</p> Signup and view all the answers

Why is acquiring data using sensors considered easy compared to the task of labeling the data?

<p>Acquiring data using sensors is straightforward, but labeling the data is complicated.</p> Signup and view all the answers

What is a common use of sensor data in the context of machine learning tasks?

<p>Detecting anomalies in processes or faults</p> Signup and view all the answers

What factors should be considered when choosing the type of chart or diagram to use for data visualization?

<p>Data type (nominal/numeric), number of dimensions, intended purpose, and the audience</p> Signup and view all the answers

How can graphs sometimes mislead viewers in data representation?

<p>Graphs can be misleading and exaggerate trends.</p> Signup and view all the answers

What is the significance of correlation analysis in exploratory statistics?

<p>Correlation analysis reveals relationships between different sensor data and their correlations with other variables like Remaining Useful Life (RUL).</p> Signup and view all the answers

Why are high positive and negative correlations between sensor data important in exploratory data analysis?

<p>High correlations indicate potential redundancy in the information provided by those sensors.</p> Signup and view all the answers

What hypothesis was developed regarding the aging of aircraft engines based on sensor data analysis?

<p>The aging of aircraft engines can be seen in the sensor curves T50, P30, Ps30, and phi.</p> Signup and view all the answers

What are the three types of classification for measurement errors?

<p>Systematic errors, random errors, dynamic errors</p> Signup and view all the answers

What is the main challenge in classifying measurement errors?

<p>Having only the sensor's information</p> Signup and view all the answers

Define SNR (Signal to Noise Ratio) in the context of measurement errors.

<p>Ratio of Signal Power to Noise Power</p> Signup and view all the answers

What is the impact of imbalanced data on classification data sets?

<p>Imbalanced data poses a common problem in classification tasks.</p> Signup and view all the answers

Provide an example scenario where imbalanced data can be a challenge.

<p>Fault diagnosis for predictive maintenance</p> Signup and view all the answers

What are the key indicators of aging in aircraft engines based on the sensor data described?

<p>Increase in temperature (T50) and decrease in pressure (P30)</p> Signup and view all the answers

How do pair plots assist in understanding the relationship between features in the context of aircraft engines?

<p>Pair plots help reveal negative correlations between features like T50 and P30, and show that the relationship with Remaining Useful Life (RUL) is time-dependent.</p> Signup and view all the answers

Explain the impact of RUL value on the correlations between features in aircraft engines' sensor data.

<p>Low RUL shows positive correlation to P30 and negative correlation to T50, while high RUL does not exhibit correlation to the sensor data.</p> Signup and view all the answers

What does the existence of time-dependent correlations reveal about the sensor data analysis for aircraft engines?

<p>Time-dependent correlations indicate that the relationships between features change over time, which is not evident when using only the Pearson correlation coefficient.</p> Signup and view all the answers

How does the confirmation of the hypothesis regarding aging in aircraft engines impact predictive maintenance strategies?

<p>The confirmation allows for the early detection of faults or aging based on temperature and pressure changes, enabling proactive maintenance interventions.</p> Signup and view all the answers

What is the main purpose of considering the acquisition of necessary data right from the start when using machine learning in engineering?

<p>To ensure an appropriate amount of data is available.</p> Signup and view all the answers

What are the key components involved in data acquisition for modeling and simulation purposes in engineering?

<p>Physical System, Sensors, Digital Acquisition System, Data Transport &amp; Storage, Signal Processing, Amplification, Filtering, AD Conversion</p> Signup and view all the answers

What does GIGO stand for in the context of data preprocessing and modeling?

<p>Garbage in, garbage out</p> Signup and view all the answers

What is the significance of understanding the values and their distribution for each attribute in data preprocessing?

<p>To ensure data quality and reliability.</p> Signup and view all the answers

Why is data collection from existing databases considered a useful and inevitable step in data preprocessing?

<p>It provides valuable existing datasets for analysis and modeling.</p> Signup and view all the answers

What is the primary source of data for data acquisition in engineering processes?

<p>Physical System</p> Signup and view all the answers

What role do sensors play in data acquisition for machine learning applications?

<p>They capture real-world data for analysis.</p> Signup and view all the answers

What are the steps involved in digital acquisition system (DAQ) as part of data acquisition in engineering?

<p>Data Transport &amp; Storage, Signal Processing, Amplification, Filtering, AD Conversion</p> Signup and view all the answers

Why is investigating outliers important in Remaining Useful Life (RUL) prediction?

<p>To ensure accurate predictions and reliability of the model.</p> Signup and view all the answers

What challenges are associated with acquiring data using sensors compared to labeling the data?

<p>Ensuring data quality and reliability.</p> Signup and view all the answers

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