Browsing by Author "Sampath, Suresh"

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    Influence of Fouling on Compressor Dynamics: Experimental and Modelling Approach
    (The American Society of Mechanical Engineers, 2017-07-24) Jombo, Gbanaibolou; Pecinka, Jiri; Sampath, Suresh; Mba, David
    The effect of compressor fouling on the performance of a gas turbine has been the subject of several papers; however, the goal of this paper is to address a more fundamental question of the effect of fouling, which is the onset of unstable operation of the compressor. Compressor fouling experiments have been carried out on a test rig refitted with TJ100 small jet engine with centrifugal compressor. Fouling on the compressor blade was simulated with texturized paint with average roughness value of 6 microns. Compressor characteristic was measured for both the clean (baseline) and fouled compressor blades at several rotational speeds by throttling the engine with variable exhaust nozzle. A Greitzer-type compression system model has been applied based on the geometric and performance parameters of the TJ100 small jet engine test rig. Frequency of plenum pressure fluctuation, the mean disturbance flow coefficient and pressure-rise coefficient at the onset of plenum flowfield disturbance predicted by the model was compared with the measurement for both the baseline and fouled engine. Model prediction of the flowfield parameters at inception of unstable operation in the compressor showed good agreement with the experimental data. The results proved that used simple Greitzer model is suitable for prediction of the engine compressor unstable behaviour and prediction of the mild surge inception point for both the clean and the fouled compressor.
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    Instantaneous failure mode remaining useful life estimation using non-uniformly sampled measurements from a reciprocating compressor valve failure
    (Elsevier, 2018) Loukopoulosa, Panagiotis; Zolkiewski, George; Bennett, Ian; Sampath, Suresh; Pilidisa, Pericles; Li, X.; Mba, David
    One of the major targets in industry is minimisation of downtime and cost, and maximisation of availability and safety, with maintenance considered a key aspect in achieving this objective. The concept of Condition Based Maintenance and Prognostics and Health Management (CBM/PHM) , which is founded on the principles of diagnostics, and prognostics, is a step towards this direction as it offers a proactive means for scheduling maintenance. Reciprocating compressors are vital components in oil and gas industry, though their maintenance cost is known to be relatively high. Compressor valves are the weakest part, being the most frequent failing component, accounting for almost half maintenance cost. To date, there has been limited information on estimating Remaining Useful Life (RUL) of reciprocating compressor in the open literature. This paper compares the prognostic performance of several methods (multiple linear regression, polynomial regression, Self-Organising Map (SOM), K-Nearest Neighbours Regression (KNNR)), in relation to their accuracy and precision, using actual valve failure data captured from an operating industrial compressor. The SOM technique is employed for the first time as a standalone tool for RUL estimation. Furthermore, two variations on estimating RUL based on SOM and KNNR respectively are proposed. Finally, an ensemble method by combining the output of all aforementioned algorithms is proposed and tested. Principal components analysis and statistical process control were implemented to create T^2 and Q metrics, which were proposed to be used as health indicators reflecting degradation processes and were employed for direct RUL estimation for the first time. It was shown that even when RUL is relatively short due to instantaneous nature of failure mode, it is feasible to perform good RUL estimates using the proposed techniques.
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    Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements
    (Elsevier, 2017-12-14) Loukopoulosa, Panagiotis; Zolkiewski, George; Bennett, Ian; Sampath, Suresh; Pilidisa, Pericles; Duan, Fang; Sattar, Tariq; Mba, David
    Reciprocating compressors are critical components in the oil and gas sector, though their maintenance cost is known to be relatively high. Compressor valves are the weakest component, being the most frequent failure mode, accounting for almost half the maintenance cost. One of the major targets in industry is minimisation of downtime and cost, while maximising availability and safety of a machine, with maintenance considered a key aspect in achieving this objective. The concept of Condition Based Maintenance and Prognostics and Health Management (CBM/PHM) which is founded on the diagnostics and prognostics principles, is a step towards this direction as it offers a proactive means for scheduling maintenance. Despite the fact that diagnostics is an established area for reciprocating compressors, to date there is limited information in the open literature regarding prognostics, especially given the nature of failures can be instantaneous. This work presents an analysis of prognostic performance of several methods (multiple linear regression, polynomial regression, K-Nearest Neighbours Regression (KNNR)), in relation to their accuracy and variability, using actual temperature only valve failure data, an instantaneous failure mode, from an operating industrial compressor. Furthermore, a variation for Remaining Useful Life (RUL) estimation based on KNNR, along with an ensemble technique merging the results of all aforementioned methods are proposed. Prior to analysis, principal components analysis and statistical process control were employed to create T^2 and Q metrics, which were proposed to be used as health indicators reflecting degradation process of the valve failure mode and are proposed to be used for direct RUL estimation for the first time. Results demonstrated that even when RUL is relatively short due to instantaneous nature of failure mode, it is feasible to perform good RUL estimates using the proposed techniques.