Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Oral malodour – background and diagnostics

Bad breath or oral malodour can be related to gingival diseases, trimethylaminuria, various inflammation diseases of upper respiratory tract, foreign bodies in nasal cavity etc. Bad breath is usually, in 85 % to 95 % of cases, inflicted by gram negative anaerobic bacteria in tongue coating. These bacteria have a tendency of producing foul-smelling sulphur containing gases called volatile sulphur compounds or VSC. Main cause of bad breath is parodontitis or postnasal drip into posterior part of the tongue. Detecting bad breath is most efficiently done by organoleptic method. By skilled analyser the reason for oral malodour can be determined with great accuracy. For scientific study the most effective method is gas chromatography (GC) with flame photometric detector (FPD). With it almost every component of exhaled air can be detected both quantitative and qualitative. Effective chairside methods include portable sulphur monitors and saliva tests.

Plasma diagnostics of the high pressure oxygen-sputtering process

The characteristics of the high pressure oxygen-sputtering plasma in the pressure range 0.8–2.4 mbar have been studied using the Langmuir probe technique. The variation in plasma parameters such as positive ion density, electron density, mean electron energy and floating potential with pressure and temperature has been investigated. It has been observed that the positive ion density increases at high substrate temperatures whereas the negative ion density decreases. The study of the variation in mean electron energy and floating potential also indicated the possibility that the number of negative ions is less when the substrates are at elevated temperatures. Since the negative ions are supposed to cause re-sputtering and make the films off-stoichiometric, the reduction in the negative ion density as observed at elevated substrate temperatures is better suited for depositing stoichiometric YBa2Cu3O7−δ superconducting thin films.

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Root cause diagnostics using temporal data mining

A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence.

Structural health monitoring of aerospace structural components using wave propagation based diagnostics

The paper discusses a wave propagation based method for identifying the damages in an aircraft built up structural component such as delamination and skin-stiffener debonding. First, a spectral finite element mode l (SFEM) is developed for modeling wave propagation in general built-up structures by using the concept of assembling 2D spectral plate elements. The developed numerical model is validated using conventional 2-D FEM. Studies are performed to capture the mode coupling,that is, the flexural-axial coupling present in the wave responses. Lastly, the damages in these built up structures are then identified using the developed SFEM model and the measured responses using the concept Damage Force Indicator (DFI) technique.

In-cylinder investigations and analysis of a SI gas engine fuelled with H-2 and CO rich syngas fuel: Sensitivity analysis of combustion descriptors for engine diagnostics and control

The sensitivity of combustion phasing and combustion descriptors to ignition timing, load and mixture quality on fuelling a multi-cylinder natural gas engine with bio-derived H-2 and CO rich syngas is addressed. While the descriptors for conventional fuels are well established and are in use for closed loop engine control, presence of H-2 in syngas potentially alters the mixture properties and hence combustion phasing, necessitating the current study. The ability of the descriptors to predict abnormal combustion, hitherto missing in the literature, is also addressed. Results from experiments using multi-cylinder engines and numerical studies using zero dimensional Wiebe function based simulation models are reported. For syngas with 20% H-2 and CO and 2% CH4 (producer gas), an ignition retard of 5 +/- 1 degrees was required compared to natural gas ignition timing to achieve peak load of 72.8 kWe. It is found that, for syngas, whose flammability limits are 0.42-1.93, the optimal engine operation was at an equivalence ratio of 1.12. The same methodology is extended to a two cylinder engine towards addressing the influence of syngas composition, especially H-2 fraction (varying from 13% to 37%), on the combustion phasing. The study confirms the utility of pressure trace derived combustion descriptors, except for the pressure trace first derivative, in describing the MBT operating condition of the engine when fuelled with an alternative fuel. Both experiments and analysis suggest most of the combustion descriptors to be independent of the engine load and mixture quality. A near linear relationship with ignition angle is observed. The general trend(s) of the combustion descriptors for syngas fuelled operation are similar to those of conventional fuels; the differences in sensitivity of the descriptors for syngas fuelled engine operation requires re-calibration of control logic for MBT conditions. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Optical diagnostics of fuel-air mixing and vortex formation in a cavity combustor

The current work reports optical diagnostic measurements of fuel-air mixing and vortex structure in a single cavity trapped vortex combustor (TVC). Specifically, the mixture fraction using acetone PLIF technique in the non-reacting flow, and PIV measurements in the reacting flow are reported for the first time in trapped vortex combustors. The fuel-air momentum flux ratio, where the air momentum corresponds to that entering the cavity through a specially-incorporated flow guide vane, is used to characterize the mixing. The acetone PLIF experiments show that at high momentum flux ratios, the fuel-air mixing in the cavity is very minimal and is enhanced as the momentum flux ratio reduces, due to a favourable vortex formation in the cavity. Stoichiometric mixture fraction surfaces show that the mixing causes the reaction surfaces to shift from non-premixed to partially-premixed stratified mixtures. PIV measurements conducted in the non-reacting flow in the cavity further reinforce this observation. The scalar dissipation rates of mixture fraction were compared with the contours of RMS of fluctuating velocity and showed very good agreement. The regions of maximum mixing are observed to be along the fuel air interface. Reacting flow Ply measurements which differ substantially from the non-reacting cases primarily because of the heat release from combustion and the resulting gas expansion show that the vortex is displaced from the centre of the cavity towards the guide vane. Overall, the measurements show interesting features of the flow including the presence of the dual cavity structure and lead to a clear understanding of the underlying physics of the cavity flow highlighting the importance of the fuel-air momentum ratio parameter. (C) 2014 Elsevier Inc. All rights reserved.

QUANTITATIVE OH PLANAR LASER INDUCED FLUORESCENCE DIAGNOSTICS OF SYNGAS AND METHANE COMBUSTION IN A CAVITY COMBUSTOR

The current work reports quantitative OH species concentration in the cavity of a trapped vortex combustor (TVC) in the context of mixing and flame stabilization studies using both syngas and methane fuels. Planar laser induced fluorescence (PLIF) measurements of OH radical obtained using a Nd: YAG pumped dye laser are quantified using a flat flame McKenna burner. The momentum flux ratio (MFR), defined as the ratio of the cavity fuel jet momentum to that of the guide vane air stream, is observed to be a key governing parameter. At high MFRs similar to 4.5, the flame front is observed to form at the interface of the fuel jet and the air jet stream. This is substantiated by velocity vector field measurements. For syngas, as the MFR is lowered to similar to 0.3, the fuel-air mixing increases and a flame front is formed at the bottom and downstream edge of the cavity where a stratified charge is present. This trend is observed for different velocities at similar equivalence ratios. In case of methane combustion in the cavity, where the MFRs employed are extremely low at similar to 0.01, a different mechanism is observed. A fuel-rich mixture is now observed at the center of the cavity and this mixture undergoes combustion. On further increase of the cavity equivalence ratio, the rich mixture exceeds the flammability limit and forms a thin reaction zone at the interface with air stream. As a consequence, a shear layer flame at the top of the cavity interface with the mainstream is also observed. The equivalence ratio in the cavity also determines the combustion characteristics in the case of fuel-air mixtures that are formed as a result of the mixing. Overall, flame stabilization mechanisms have been proposed, which account for the wide range of MFRs and premixing in the mainstream as well.