It is very difficult to share datasets for condition based and predictive maintenance applications due to the commercial sensitivity of the data involved. We have published a number of datasets that we generated together with Flow Center of Excellence. Next to these there are some good resources available on the internet if you want to learn how to apply (advanced) analytics on data for a CBM/PdM project.
These are our favourite open datasets:
1. UWA System Health Lab
The data sets provided by the System Health Lab of the Faculty of Engineering and Mathematical Sciences at the University of Western Australia. The faculty provides different datasets that can be used to learn how to apply classification and anomaly detection methods.
The datasets are well described and after sign-on you get access.
Each of the datasets is individually described.
3. UCI Machine Learning Repository
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. The archive has been around for decades and you can find interesting data, for CBM/PdM, in the engineering data sets:
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