Predictive Maintenance

• Accessing and preprocessing data from a variety of sources

• Using machine learning to develop predictive models

• Creating dashboards for visualizing and interacting with model results

• Deploying predictive algorithms in production systems and embedded devices

• Using simulation to generate data for expensive or hard-to-reproduce failures

For this session will run through battery modeling and parameterization, SOC and SOH estimation and lastly determination of its remaining useful life through predictive maintenance algorithm

Highlights:

You will be able to learn:

Predictive maintenance allows equipment operators and manufacturers to assess the condition of machines, diagnose faults, and estimate time to failure. Because machines are increasingly complex and generate large amounts of data, many engineers are exploring deep learning approaches to achieve the best predictive results.

• Anomaly detection of industrial equipment using vibration data
• Condition monitoring of an air compressor using audio data

Highlights:

This workshop is suitable for anyone who are interested in learning about the workflow for developing PdM algorithms with MATLAB and Simulink.

In this hands-on workshop, you will be able to learn:

• Generating data from Simulink
• Data pre-processing and feature extraction 
• Implementing feature extraction 
• Predictive modeling 

*Terms and Conditions:

• Due to the limited availability of seats, early registration is strongly recommended to ensure your participation.
• Registration will be confirmed upon your receipt of the confirmation, on a first-come-first-serve basis.
• Should you wish to cancel your registration, please inform us in writing to events@techsource-asia.com
• TechSource reserves the right to reschedule or cancel the event due to unforeseen circumstances. Every effort, however, will be made to inform participants of the change.