Application of morphological analysis for gear fault detection and trending

Frequency domain based signal processing methods such as cepstrum analysis, Hilbert Transform based demodulation, cyclostationary analysis, etc have been shown to present a quite effective behaviour in the detection of defects, when applied to the analysis of vibration signals, resulting from gear pairs with one or more defective gears. However, these methods typically require some complex and sophisticated analysis, which renders their application cumbersome for applications requiring unskilled personnel or automated fault detection and trending. Alternatively to these methods, morphological analysis for processing vibration signals has been proposed, addressing the issues of how to quantify the shape and the size of the signals directly in the time domain. Morphological analysis and the resulting morphological index is applied in this paper to a set of twelve successive vibration measurements resulting from a gearbox prior to tooth breakage. As shown, the morphological index is able monitor the evolution of the potential fault, providing a clear warning prior to the breakage of the tooth

Vibration based condition monitoring of wind turbine gearboxes based on cyclostationary analysis

Wind industry experiences a tremendous growth duringthe last few decades. As of the end of 2016, the worldwidetotal installed electricity generation capacity from wind poweramounted to 486,790 MW, presenting an increase of 12.5%compared to the previous year. Nowadays wind turbinemanufacturers tend to adopt new business models proposingtotal health monitoring services and solutions, using regularinspections or even embedding sensors and health monitoringsystems within each unit. Regularly planned or permanentmonitoring ensures a continuous power generation and reducemaintenance costs, prompting specific actions when necessary.The core of wind turbine drivetrain is usually a complicatedplanetary gearbox. One of the main gearbox componentswhich are commonly responsible for the machinery breakdownsare rolling element bearings. The failure signs of an earlybearing damage are usually weak compared to other sources ofexcitation (e.g. gears). Focusing towards the accurate and earlybearing fault detection, a plethora of signal processing methodshave been proposed including spectral analysis, synchronousaveraging and enveloping. Envelope analysis is based on theextraction of the envelope of the signal, after filtering arounda frequency band excited by impacts due to the bearing faults.Kurtogram has been proposed and widely used as an automaticmethodology for the selection of the filtering band, being onthe other hand sensible in outliers. Recently an emerging Address all correspondence to this author.interest has been focused on modelling rotating machinerysignals as cyclostationary, which is a particular class of nonstationary stochastic processes. Cyclic Spectral Correlation andCyclic Spectral Coherence have been presented as powerfultools for condition monitoring of rolling element bearings,exploiting their cyclostationary behaviour. In this work a newdiagnostic tool is introduced based on the integration of theCyclic Spectral Coherence along a frequency band that containsthe diagnostic information. A special procedure is proposedin order to automatically select the filtering band, maximizingthe corresponding fault indicators. The effectiveness of themethodology is validated using the National Renewable EnergyLaboratory (NREL) wind turbine gearbox vibration conditionmonitoring benchmarking dataset which includes various faultswith different levels of diagnostic complexity.status: publishe

Condition monitoring of rotating machinery under varying operating conditions based on Cyclo-Non-Stationary Indicators and a multi-order probabilistic approach for Instantaneous Angular Speed tracking

International audienc

Design of a mechanical system for energy transfer between acoustic fields by frictional contact nonlinearity

The aim of this work is to investigate the energy transfer between acoustic fields, through a contact interface by exploiting the friction nonlinearities. In particular, the work is focused on the development of a device able to transfer the vibrational energy from a known primary vibrational field to a secondary field with a different frequency content. The device is composed by a main resonator capturing the energy from the primary vibrational field and a secondary resonator, excited by the large band excitation at the frictional interface and radiating the secondary vibrational field. The main resonator has been designed as a compliant system able to provide a translational oscillation of the contact surface, allowing for maintaining constant the normal load at the interface.The numerical design of the device has been developed together with its experimental dynamic characterization. Experimental tests, developed on a dedicated set-up, showed the reliability of the device to perform the energy transfer between the vibrational fields

Least action criteria for blind separation of structural modes

It was recently shown that blind source separation (BSS), as originally developed in the signal processing community, can be used in operational modal analysis to separate the responses of a structure into its individual modal contributions. This, in turn, allows the application of simple single-of-degree-freedom techniques to identify the modal parameters of interest. Several publications have recently attempted to give a posteriori physical interpretations to BSS – as initially developed in telecommunication signal processing – when applied to the field of structural dynamics. This paper proposes to follow the route the other way round. It shows that several separation criteria purposely dedicated to operational modal analysis can be deduced from general physical considerations. Three such examples are introduced, based on very different properties that uniquely characterise a structural mode. The first criterion, coined the “principle of shortest envelope”, conjectures that the envelope of a modal response has, among all possible envelopes, the shortest length. That such a principle leads to the governing differential equation of a single-degree-of-freedom oscillator is proved from calculus of variation. The second criterion, coined the “principle of minimum spectral variance”, conjectures that the frequency spectrum of a structural mode is maximally concentrated around its central frequency. Finally, the third criterion, coined the “principle of least spectral complexity”, states that a structural mode has the lowest possible entropy in the frequency domain. All three criteria can be expressed in terms of a mixing matrix whose columns contain the unknown mode shapes. The recovery of the latter is then trivially achieved by minimising the criteria. Extensive simulations show that the proposed criteria lead to figures of merit very similar to those of the state-of-the-art, while at the same time providing physical insight that other algorithms issued form the signal processing community may dramatically lack

Assessment of Combustion Mechanical Noise Separation Techniques on a V8 Engine

Copyright © 2017 SAE International. The noise radiated by an ICE engine results from a mixture of various complex sources such as combustion, injection, piston slap, turbocharger, etc. Some of these have been categorized as combustion related noise and others as mechanical noise. Of great concern is the assessment of combustion noise which, under some operating conditions, is likely to predominate over the other sources of noise. The residual noise, produced by various other sources, is commonly referred to as mechanical noise. Being able to extract combustion and mechanical noise is of prime interest in the development phase of the engine and also for diagnostic purposes. This paper presents the application of combustion mechanical noise separation techniques on a V8 engine. Three techniques, namely the multi regression analysis, the classical Wiener filter and the cyclostationary (synchronous) Wiener filter, have been investigated. The techniques have been applied to microphone recordings measured at one meter distance from an engine running on a test bench. Reference in-cylinder pressure sensors have been instrumented and synchronously acquired together with the microphones. Strengths and weaknesses of the techniques are assessed and presented in the paper. Finally a source separation technique is applied as a pre-processing step to the sound recordings measured on a microphone array. Sound source localization then allows to localize and quantify the combustion and mechanical sources of noise on the engine. This is illustrated with an application example.status: publishe