Gearboxes are critical elements of mechanical systems that are widely used in aerospace, energy generation, land and naval applications. The early detection of changes in the technical condition of this equipment is of great importance for the optimisation of maintenance costs. Vibration signal components resulting from the presence of the developing faults of meshing gears contain the information that, once extracted from the signal, may allow for a reliable estimation of the technical condition of the meshing gears. Wavelet bicoherence (WB)-based technology has been used to obtain the signal feature characterising the phase relationship between the signal components generated by gear faults in the selected frequency bandwidths. In previous research, WB has been successfully applied to the detection of artificiallycreated gearbox faults. This paper will present the application of WB in the detection of naturally-developing gear faults.

Novel vibration sensor-based diagnostic technologies, built on the higher order wavelet spectral cross-correlation (WSC), are proposed, investigated and applied to gearbox vibration diagnosis for the first time in worldwide terms. The proposed WSC-based technologies do not feature any constrains in selection of signal spectral components, relations between which are analysed. That is a radical improvement in comparison with the higher-order spectra (HOS). The WSC technologies are applied for an experimental diagnosis of a local gear tooth fault of a helical gearbox that is developed during a long duration gearbox endurance test. Differences between the applied technologies and advantages of the novel WSC approach over the classical HOS are explained in detail. Superiority of the WSC technologies is justified by high validity comprehensive experimental comparison with the HOS technologies: i.e., the wavelet bicoherence and the wavelet tricoherence.

Higher order spectra exhibit a powerful detection capability of low-energy fault-related signal components, buried in background random noise. This paper investigates the powerful nonlinear non-stationary instantaneous wavelet bicoherence for local gear fault detection. The new methodology of selecting frequency bands that are relevant for wavelet bicoherence fault detection is proposed and investigated. The capabilities of wavelet bicoherence are proven for early-stage fault detection in a gear pinion, in which natural pitting has developed in multiple pinion teeth in the course of endurance gearbox tests. The results of the WB-based fault detection are compared with a stereo optical fault evaluation. The reliability of WB-based fault detection is quantified based on the complete probability of correct identification. This paper is the first attempt to investigate instantaneous wavelet bicoherence technology for the detection of multiple natural early-stage local gear faults, based on comprehensive statistical evaluation of the industrially relevant detection effectiveness estimate—the complete probability of correct fault detection.

This paper introduces a novel approach to monitor pressure dynamics in turbomachinery. This innovation is motivated by the need expressed by machine OEMs and end-users to detect and avoid combustion instabilities, as well as lean-blowout (LBO), in low emission combustion systems. Such situations are often characterised by a marked increase of pressure signals in low frequency range. The piezoelectric technology, conventionally used for pressure measurements, presents sensitivity and stability issues at high temperatures and low frequencies. Here a new paradigm for pressure sensing, based on optical interferometry, is characterised and validated. The interferometric sensing system is designed to provide a larger range of measurement frequencies with better performance, in the low frequency range (< 50Hz), while exposed to high temperatures. This unique feature allows the real-time observation of events, such as the specific behaviour of a low frequency flame dynamic, which is characteristic of an imminent LBO. This improved monitoring system will support an optimisation of the machine performance, leading to a safer, cleaner, more flexible and more cost-efficient operation for the end-user. The novel measurement system has been characterised under non-reactive and reactive conditions within the frame of a joint study between Meggitt SA, Combustion Bay One e.U. and FH Joanneum GmbH. The technology is first described, including the relevant hardware and software components of the measurement chain. The different experimental set-ups and conditions are also illustrated. The results of the test campaign and their subsequent analysis are then presented, supporting the expected advantages over piezoelectric technology. In conclusion, a possible strategy for the detection of LBO precursors based on low frequency data is proposed.

This paper introduces a novel approach to monitor combustion instabilities in turbomachinery. This innovation is motivated by the need to better analyze flame health in a continuous flow machine, and more precisely in its hot core expressed by machine OEMs and end-users. This improved monitoring system will support an optimization of the machine performance, leading to a safer, cleaner, more flexible and more cost-efficient operation for the end-user. There have been several numerical studies that simulate the nonlinear dynamics of flame instabilities limit in simple combustors, they predict the pressure oscillations frequency is very low 5-25 Hz. Nowadays, in gas turbine monitoring, dynamic pressure measurement sensors are based on electrical working principle technologies such as piezoelectric, piezo-resistive and capacitive measurement. While exposed to high temperatures, due to pyro-electric effects and noise spectral density of charge amplifiers, piezo sensors signal to noise ratio (SNR) decreases sharply at low frequencies (about a factor 10 every 100°). Optical sensing systems provide much better stability, in the low frequency range when exposed to high temperature and, moreover, are intrinsically insensitive to vibration or EMI perturbation. This feature allows analyzing more accurately low frequency flame dynamics. Within the frame of a joint study between Meggitt, Combustion Bay One e.U. and FH Joanneum GmbH, the behavior of an optical measurement system was tested under different combustion instability conditions. By acting on system parameters (equivalent ratio, air speed) several tests have been conducted where combustion has been driven to different instability conditions such as premixed to diffusion flame transition, lean blow out, flashback. Data have been recorded and analysed from both the optical and the piezo sensors installed within the combustion chamber. The objective of the test campaign is twofold: compare optical to piezo system performances under flame combustion instabilities and, taking advantage of improved low frequency SNR of pressure data coming from optical sensors, to develop and validate an algorithmic strategy to detect/prognose phenomena such as Lean Blow Out and Flashback. The paper initially describes the principia of the used optical sensing technology, including some relevant hardware and software aspects of the measurement chain.  After that, the experimental set-up and tests conditions are presented. About piezo to optical data comparison, SNR analysis of test data confirms the expectations of a lower noise at low frequency and the improved visibility of flame instabilities provided by optical sensor. Based on this, in order to analyze the transient behavior at low frequencies associated to flame instabilities two algorithmic strategies have been developed: wavelet analysis and chaos dimension analysis. Based on these methodologies several Lean Blow Out indicators have been implemented and tested.  Details of their behavior in response to the variation of the equivalence ratio close to the flame blow out are presented and discussed. Three of the proposed indicators, under the investigated test conditions, proved to possess the capability to detect the blow out event.  Depending on how the approach to the blow out event occurs, some indicators also shown prognostics capability.  Results show some indicators start reacting as the flame approaches to extinction or as the equivalence ratio reduces.  These indicators can be considered flame health meters. The test campaign results shown in the paper allow to conclude that optical sensing technologies provide advantages over piezoelectric sensing technologies such as:  insensitivity to pyro-electric effects and inherent insensitivity to external perturbations, i.e. electromagnetic interferences and radio frequency interferences, vibrations. Particularly the improved accuracy at low frequencies of the sensor coupled with new signal processing techniques, as the ones presented, may support a flame health monitoring capability and the ability to sense blowout precursors. The replacement of piezo-electric with fiber optic sensors will therefore be desirable for many combustion monitoring applications, especially the ones requiring monitoring of low frequencies. This can, provide significant payoffs in engine reliability and operability, in enabling optimal performance over extended time periods as an engine ages, in reducing maintenance costs, and in increasing engine life.