Wael Moussa to present next Wednesday

Next up in our line-up of speakers is Wael Moussa. Wael will be giving a talk on Thermography-Assisted Bearing Condition Monitoring.

Time: 1:00pm

Date: Wednesday July 3rd

Location: CBY B205

I hope to see you all there!

Thermography-Assisted Bearing Condition Monitoring

Wael Moussa


Bearings are widely used in almost all rotational mechanical systems. The monitoring their conditions are crucial to reliable operations. Although temperature monitoring methods were previously judged as low responsive approaches to mechanical system condition assessment, the advancement of temperature sensing devices and the recent results in rolling contact tribology encourage the revisit of these methods.

In this study two systems are implemented respectively using thermography and infrared sensor for detection of the bearing faults based on temperature rise curve during thermal transient period before reaching the thermal equilibrium condition. The results are compared with the finite element model developed using the ANSYS workbench software. It is shown that, although the equilibrium temperature for bearing outer surface is not sensitive to different bearing faults, the temperature rise curve during thermal transient period is sensitive to all bearing faults.  Furthermore, this transient curve is useful in finding lubricant performance and specifying optimum lubricant volume for every operating condition.

To further exploit the rich information provided by the data during the thermal transient period, a system that stimulates such a transient behavior is proposed. This is done by changing the temperature of the bearing surrounding environment using surface heaters . The results have shown a great similarity between the stimulated transient behavior and the actual one observed at the beginning of the bearing operations. It is also shown that bearing faults can be detected even after the bearing enters its thermal equilibrium condition.

This study has demonstrated that the temperature-based approach can effectively detect lubrication deficiency long before a physical bearing fault develops. As the lubricant deficiency eventually causes physical bearing damages, this makes the temperature-based approaches particularly effective in early fault detection, thought such approaches tend to be less responsive to actual physical damages themselves.

Farid Sheikhi presented last week

Farid Sheikhi presented his MASc thesis seminar last week.  Supervisor Davide Spinello was teaching at the time so was unable to attend.  Click on the photo for a larger version.

Farid after presenting his thesis seminar.  Missing from the photo is supervisor Dr. Davide Spinello.

Farid after presenting his thesis seminar. Missing from the photo is supervisor Dr. Davide Spinello.

Farid Sheikhi to present Wednesday the 19th

The next speaker in our student seminar series will be Farid Sheikhi.  Farid will be giving a talk titled “Entropy Filter for Anomaly Detection with Eddy Current Remote Field Sensors”.

Where: CBY B205

Date: Wednesday June 19th, 2013

Time: 13:00

The seminar of the talk is given below.  Hope to see you all there!

Entropy Filter for Anomaly Detection with Eddy Current Remote Field Sensors

Candidate: Farid Sheikhi
Supervisor: Dr. Davide Spinello


We consider the problem of extracting a specific feature from a noisy signal generated by a multi-channels Remote Field Eddy Current Sensor. The sensor is installed on a mobile robot whose mission is the detection of anomalous regions in metal pipelines. Given the presence of noise that characterizes the data series, anomaly signals could be masked by noise and therefore difficult to identify in some instances. In order to enhance signal peaks that potentially identify anomalies we consider an entropy filter built on a posteriori probability density functions associated with data series. Thresholds based on the Neyman-Pearson criterion for hypothesis testing are derived. The algorithmic tool is applied to the analysis of data from a portion of pipeline with a set of anomalies introduced at predetermined locations. Critical areas identifying anomalies capture the set of damaged locations, demonstrating the effectiveness of the filter in detection with Remote Field Eddy Current Sensor.