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Condition monitoring of rolling element bearings during low and variable speed conditions

Andreas Klausen disputerer for ph.d.-graden med avhandlingen “Condition monitoring of rolling element bearings during low and variable speed conditions” tirsdag 14. mai 2019. (Foto: Privat)

I have developed two new algorithms for fault detection during low and variable speeds in addition to a new algorithm to estimate the maintenance window for a ball bearing. This is important information as it allows for machine maintenance planning. These algorithms are general and should be useful on several kinds of rotating equipment.

Andreas Klausen

PhD-Candidate and Assistant Professor

Andreas Klausen at the Faculty of Engineering and Science has submitted his thesis entitled "Condition monitoring of rolling element bearings during low and variable speed conditions” and will defend the thesis for the PhD-degree Tuesday 14 May 2019.

He has followed the PhD-programme at the Faculty of Engineering and Science  with Specialisation i Mechatronics.

Summary of the thesis by Andreas Klausen:

Condition monitoring of rolling element bearings during low and variable speed conditions

Rolling element bearings are machine components installed in almost all rotating equipment. They are the link between rotating shafts and stationary housing.

This is how rolling element bearings work

One application is between the suspension and axle of a car.

Ball bearings are composed of four main parts: an inner ring attached to the shaft; an outer ring mounted in a stationary housing; several balls rotating between the raceways; and a train cage to keep the balls apart.

When the shaft rotates, the rolling elements rotate on the surface of the inner and outer races and distributes the load from the shaft to the stationary housing.

To minimise friction in the ball bearing it must be lubricated with oil or bearing grease. Even if the bearing is well greased, it will become worn over time.

Expensive replacements just in case

The time it takes before the bearing needs to be replaced is difficult to estimate, that is why the bearing is often replaced at a frequency giving good margins for survival, or when the bearing is broken.

In the case of big expensive machines, waiting until the bearing breaks down is not favourable, however replacing it long before it is necessary is also costly.

In any case, bearing failure can occur unexpectedly between services.

That is why it is important to monitor the bearing condition with the aid of sensors and algorithms.

Vibration indicates damage

The illustration below shows a ball bearing with outer ring damage. Every time a ball rolls over the damaged surface the bearing vibrates. This is measured on a bearing vibration tester as shown.

The readings are analysed on a computer, and pulses of high vibration with a certain frequency indicate that there is something wrong with the bearing.

Illustrasjon: Andreas Klausen

Illustrasjon: Andreas Klausen

Condition monitoring of low speed bearings

This thesis deals with condition monitoring of rolling element bearings that operate at variable and low speeds.

Low speeds may cause problems due to the resulting low vibration energy which occurs when the balls move slowly across the damaged surface. It then becomes difficult to separate the bearing vibration from noise.

Variable speeds also pose challenges since the frequency and energy of the shocks varies over time. That makes it hard to find repeated elements in the bearing signal.

Developing algorithms to detect damage

In this thesis I have focused on developing new algorithms for bearing fault detection during these difficult conditions.

First we built a test bench to wear down rolling element bearings, and then the vibration was measured at low and variable speeds.

I have developed two new algorithms for fault detection during low and variable speeds in addition to a new algorithm to estimate the maintenance window for a ball bearing.

This is important information as it allows for machine maintenance planning.

These algorithms are general and should be useful on several kinds of rotating equipment.

The thesis is based on six scientific papers describing the test bench and the algorithms.

Disputation facts:

Kandidaten: Andreas Klausen (1991, Oslo) Bachelor degree in Mechatronics, UiA, 2013. Master degree in Mechatronics, UiA, 2015. Integrated PhD-position (desciption in Norwegian only) October 2014 to January 2019, now assistant Professor at UiA.

The trial lecture and the public defence will take place at Room C2 040, Campus Grimstad. Professor Tom Viggo Nilsen, Department of Engineering Sciences, will chair the disputation.

Trial lecture at 10:30 a.m.

Public defense at 12:30 p.m.

Given topic for trial lecture: «Particle filtering for prognostics»

Thesis title: “Condition monitoring of rolling element bearings during low and variable speed conditions

Search for the thesis in AURA - Agder University Research Archive, a digital archive of scientific papers, theses and dissertations from the academic staff and students at the University of Agder. The thesis will also be available at the University Library, and some copies will also be available for loan at the auditorium where the disputation takes place.

Opponents:

First opponent: Professor Jérôme Antoni, Lyon Tech la Doua (University of Lyon)

Second opponent: Dr. Principal Scientist Pedro Rodriguez, ABB AB, Corporate Research

Professor Joao Leal, UiA is appointed as the administrator for the assessment commitee.

Supervisors were Professor Kjell Gunnar Robbersmyr (main supervisor) og Professor Van Khang Huynh (co-supervisor)