Degradation Modelling for Predictive Maintenance - An Application to High Voltage Rotary Machines

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.