I am working on a project with Generative Adversarial Network to generate pseudo (minority) samples to expand the dataset and then using that expanded dataset to train my model for fault detection in machinery.
I have already tried my project with 2 machine temperature sensor datasets (containing timestamp and temperature data at that timestamp).
I am looking for a dataset having a similar structure (i.e timestamp with one sensor data) , For Example, Current sensor with time or pressure sensor with time.
I have searched Kaggle but most datasets on Kaggle are multivariate.
Where can I find Univariate Time-series data for fault detection in machinery?
#machinelearning #univariatedata #timeseriesdata #machinerydata #faultanalysis #faultdetection #anomalydetection #GAN #neuralnetwork
Dear Palak Nath
This article might be helpful, have a look:
https://arxiv.org/pdf/2004.00433
Regards
Qamar Ul Islam
See if Case Western Reserve University Bearing Fault Dataset works for you. They provide voltage vs time data in different motor setups.
https://csegroups.case.edu/bearingdatacenter/pages/welcome-case-western-reserve-university-bearing-data-center-website
Another one is Mechanical Engineering Construction and Drive Technology (KAt) Dataset. It contains current vs time data:
https://mb.uni-paderborn.de/en/kat/main-research/datacenter/bearing-datacenter
You can check the following bearing datasets (vibration signals Vs time):
PS: both of the dataset are treated in this paper : Article Leveraging Label Information in a Knowledge-Driven Approach ...
IMS bearing : https://ti.arc.nasa.gov/tech/dash/groups/pcoe/
prognostic-data-repository/
Wind turbine high speed shaft data: https://www.mathworks.com/help/predmaint/ug/ wind-turbine-high-speed-bearing-prognosis.html
Palak Nath
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