DeepAI AI Chat
Log In Sign Up

A Bayesian Approach for Shaft Centre Localisation in Journal Bearings

by   Christopher A. Lindley, et al.

It has been shown that ultrasonic techniques work well for online measuring of circumferential oil film thickness profile in journal bearings; unfortunately, they can be limited by their measuring range and unable to capture details of the film all around the bearing circumference. Attempts to model the film thickness over the full range of the bearing rely on deterministic approaches, which assume the observations to be true with absolute certainty. Unaccounted uncertainties of the film thickness may lead to a cascade of inaccurate predictions for subsequent calculations of hydrodynamic parameters. In the present work, a probabilistic framework is proposed to model the film thickness with Gaussian Processes. The results are then used to estimate the location of the bearing shaft under various operational conditions. A further step in the process involves using the newly-constructed dataset to generate likelihood maps displaying the probable location of the shaft centre, given the bearing rotational speed and applied static load. The results offer the possibility to visualise the confidence of the predictions and allow the true location to be found within an area of high probability within the bearing's bore.


page 12

page 13

page 14


Is profile likelihood a true likelihood? An argument in favor

Profile likelihood is the key tool for dealing with nuisance parameters ...

Entropy as a measure of attractiveness and socioeconomic complexity in Rio de Janeiro metropolitan area

Defining and measuring spatial inequalities across the urban environment...

Farm-wide virtual load monitoring for offshore wind structures via Bayesian neural networks

Offshore wind structures are subject to deterioration mechanisms through...

Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties

Machine learning techniques have been successfully applied to super-reso...

ProBF: Learning Probabilistic Safety Certificates with Barrier Functions

Safety-critical applications require controllers/policies that can guara...

cvBMS and cvBMA: filling in the gaps

With this technical report, we provide mathematical and implementational...