| dc.description.abstract | Large high voltage rotary machines are commonly utilized in gas processing plants for operations
such as dewatering and compression. The availability of these machines are very
critical as the operation down times are generally associated with expensive production
loss. Therefore this is no surprise that industries put a lot of effort in ensuring the maximum
availability of these machines. However accurate failure prediction of such machines
is challenging due to the complexity associated with technicality, data collection, testing
and condition monitoring, etc.
This project addresses such an issue regarding the high voltage motors in Kollsnes gas
processing plant that are currently in operation. It is operated by Gassco and Statoil serves
as technical service provider. Karsten Moholt AS conducts the condition monitoring and
ABB conducts the assessment of the conditions of these motors and claims to predict time
to failure of an individual machine with certain confidence level. However, this prediction
method is under the copyright of ABB and how the process works is not known by any
other party. Therefore it leaves some room for further investigations regarding estimation
of remaining useful life and in addition the current prognostics practice is limited to unit
level.
In this situation, Statoil is interested in estimating remaining useful life of the motors
due to ageing in order to reduce uncertainty regarding operation outage and to support
overall maintenance decisions. They are further interested in extending the boundary of
unit level prognostic to system level prognostic because the demand for motor operation
varies depending on the two seasonal periods- summer and winter. In addition, they would
like to explore the possibility of developing a simulator that is capable of estimate remaining
useful life of a motor (or possibly the system) under given current health condition,
previous history and future probable usage profile of the machine in order to further facilitate
maintenance decision making process.
Various approaches have been taken by researchers to address the issues in high voltage
rotary machine prognostic but there are still remaining many challenges that are making
the whole prognostic process complicated. The main focus of this thesis is to develop a
degradation model for the rotary machines in order to estimate remaining useful life under
the given current health condition and make a possible transition from unit level prognostic
to system level prognostic. The required preliminary task of prognostic estimation involves
finding a good indicator that describes the health condition of a motor reasonably well.
During the process, it s been observed that, failure due to ageing process in stator winding
insulation is the most critical failure mechanism in high voltage rotary machines and
the health of a motor basically depends on the condition of the stator winding insulation.
It s been noticed that, ageing processes can be influenced by multiple stresses acting in
synergistic fashion which makes any sort of life modeling or degradation modeling very
difficult. It s been further noticed that regardless of the stress acting most dominantly on a
failure process, the final failure usually occurs due to electrical ageing. Further progress in
the study leads to the conclusion that, partial discharge test is currently the most acceptable testing method for health condition indication of an insulation system among the available
methods.
Under the assumption that condition monitoring data is available, statistical approach
based on non-homogeneous Gamma process has been employed for the degradation modeling
in order to estimate remaining useful life of a given rotary machine. Important
properties of Gamma process has been discussed in correlation with the rotary machine
prognostic. Associated parameters have been calculated with a 95% confidence interval.
Quality of parameter estimation has been discussed for several inspection strategies. In
case of prognostic, current condition (actual degradation level) has been incorporated with
remaining useful life estimation. This is due to the fact that, condition-based prognostic
tends to be more accurate than traditional age-based prediction. Some relevant insights
have been discussed and a demonstration have been provided regarding possible transition
from unit level prognostic to system level prognostic.
Based on expert opinion provided by Statoil and literature surveys, non-homogeneous
Gamma process appears to be the most appropriate for degradation modeling of winding
insulation system utilizing partial discharge information. However reminding of the
famous quote by George E. P. Box, All models are wrong but some are useful ; proposed
model requires to go through some validation process with the help of useful field
data. Nevertheless the proposed model is full of possibilities for making transition from
a theoretical model to a more practical model as more information becomes available. In
addition, application of such degradation modeling is not only limited to this specific case.
Gamma process is already a popular choice for this purpose and non-homogeneous gamma
process have significant implications for civil engineering applications.
This thesis proposes an initial framework for prognostics of remaining useful life of
high voltage rotary machines under the assumption of non-linear degradation increment of
insulation system. It shows potential for further research leading to some interesting and
useful outcomes in this particular area of research. | |
