Utilising data effectively is crucial in solving engineering issues, like predicting when machines might fail. However, sorting through data to make these predictions isn't easy.
In this talk, Shuixiu will discuss the challenges of predicting failures from time series data and suggest ways to improve the quality of the data. By cleaning up messy data, she'll show how we can better understand when machines might break down. Additionally, the talk will explore how background noise can affect the accuracy of failure predictions using time series data.
About the speaker: Dr Shuixiu Lu received her PhD in nonlinear time series analysis for research on complex dynamics of engineered and social systems. She (Lu) is currently working on industrial data as a research follow with our centre. Her focus is on identifying tipping points and indicators of imminent changes to alert machine failures from time series data.
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Shuixiu Lu presents - Optimising failure predictions through data quality control
Utilising data effectively is crucial in solving engineering issues, like predicting when machines might fail. However, sorting through data to make these predictions isn't easy.
In this talk, Shuixiu will discuss the challenges of predicting failures from time series data and suggest ways to improve the quality of the data. By cleaning up messy data, she'll show how we can better understand when machines might break down. Additionally, the talk will explore how background noise can affect the accuracy of failure predictions using time series data.
About the speaker: Dr Shuixiu Lu received her PhD in nonlinear time series analysis for research on complex dynamics of engineered and social systems. She (Lu) is currently working on industrial data as a research follow with our centre. Her focus is on identifying tipping points and indicators of imminent changes to alert machine failures from time series data.
When - 3 May 2024 at 1.30pm
Where - Microsoft Teams Link to Microsoft Teams
Join the meeting now
Meeting ID: 467 595 503 941
Passcode: MeTFiM
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