Characterising the friction and wear between the piston ring and cylinder liner based on acoustic emission analysis

In this paper, an experimental investigation was carried out to evaluate the friction and wear between the cylinder liner and piston ring using acoustic emission (AE) technology. Based on a typical compression ignition (CI) diesel engine, four types of alternative fuels (Fischer-Tropsch fuel, methanol-diesel, emulsified diesel and standard diesel) were tested under dif-ferent operating conditions. AE signals collected from the cylinder block of the testing en-gine. In the meantime, the AE signals in one engine cycle are further segregated into small segments to eliminate the effects of valve events on friction events of cylinder liner. In this way, the resulted AE signals are consistent with the prediction of hydrodynamic lubrication processes. Test results show that there are clear evidences of high AE deviations between dif-ferent fuels. In particular, the methanol-diesel blended fuel produces higher AE energy, which indicates there are more wear between the piston ring and cylinder liner than using standard diesel. On the other hand, the other two alternative fuels have been found little dif-ferences in AE signal from the normal diesel. This paper has shown that AE analysis is an ef-fective technique for on-line assessment of engine friction and wear, which provides a novel approach to support the development of new engine fuels and new lubricants

An application of early fault detection for the crankshaft and piston of an internal combustion engine

Internal combustion engines are made of many moving components that are subjected to high inertia and combustion loads. Crankshaft bearing and piston-cylinder walls work under hydrodynamic lubrication conditions. Any failure at those bearing may cause severe damage on the engine. Acceleration measurement on the cylinder block and cylinder was effectively used for early detection of failure in hydrodynamic lubrication. Inspection of the crankshaft and piston components after the test clearly shows that metal-to-metal contact occurred during the test and real-time acceleration signal analysis can help to early detection of the problem

Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis

Air-borne acoustic based condition monitoring is a promising technique because of its intrusive nature and the rich information contained within the acoustic signals including all sources. However, the back ground noise contamination, interferences and the number of Internal Combustion Engine ICE vibro-acoustic sources preclude the extraction of condition information using this technique. Therefore, lower energy events; such as fuel injection, are buried within higher energy events and/or corrupted by background noise. This work firstly investigates diesel engine air-borne acoustic signals characteristics and the benefits of joint time-frequency domain analysis. Secondly, the air-borne acoustic signals in the vicinity of injector head were recorded using three microphones around the fuel injector (120° apart from each other) and an Independent Component Analysis (ICA) based scheme was developed to decompose these acoustic signals. The fuel injection process characteristics were thus revealed in the time-frequency domain using Wigner-Ville distribution (WVD) technique. Consequently the energy levels around the injection process period between 11 and 5 degrees before the top dead center and of frequency band 9 to 15 kHz are calculated. The developed technique was validated by simulated signals and empirical measurements at different injection pressure levels from 250 to 210 bars in steps of 10 bars. The recovered energy levels in the tested conditions were found to be affected by the injector pressure settings

Discussion on the Influence of Friction and Wear on the Reliability of Marine Diesel Engines

In view of the impact of friction and wear on the reliability of marine diesel engines, this article discusses the main causes of wear in marine diesel engines when analyzing the specific effects, including the impact of average effective pressure on friction loss, the impact of rotational speed on friction loss, the impact of cylinder number on friction loss, the impact of oil viscosity and cooling system temperature, and the impact of fuel injection pump pressure on friction loss The impact of the number of piston rings on diesel engines. In the analysis and discussion of the impact of friction and wear on the reliability of marine diesel engines, relevant suggestions were proposed for fault diagnosis, such as the application of the following diagnostic techniques: internal machine equipment gear wear fault analysis, bearing melting wear fault analysis, bearing wear deformation fault analysis, bearing pitting peeling fault analysis, diesel engine piston wear fault analysis, etc, And the following measures to avoid wear issues: reasonably reducing the speed of diesel engines, scientifically reducing the number of piston rings, and continuously optimizing the lubrication system

Evolved model for early fault detection and health tracking in marine diesel engine by means of machine learning techniques

The Coast Guard Command, which has a wide range of duties as saving human lives, protecting natural resources, preventing marine pollution and battle against smuggling, uses diesel main engines in its ships, as in other military and commercial ships. It is critical that the main engines operate smoothly at all times so that they can respond quickly while performing their duties, thus enabling fast and early detection of faults and preventing failures that are costly or take longer to repair. The aim of this study is to create and to develop a model based on current data, to select machine learning algorithms and ensemble methods, to develop and explain the most appropriate model for fast and accurate detection of malfunctions that may occur in 4-stroke high-speed diesel engines. Thus, it is aimed to be an exemplary study for a data-based decision support mechanism

Monitoring of the piston ring-pack and cylinder liner interface in diesel engines through acoustic emission measurements

Investigation of novel condition monitoring systems for diesel engines has received much recent attention due to the increasing demands placed upon engine components and the limitations of conventional techniques. This thesis documents experimental research conducted to assess the monitoring capabilities of Acoustic Emission (AE) analysis. In particular it focuses on the possibility of monitoring the piston ring-pack and cylinder liner interface, a critical engine sub-system for which there are currently few practical monitoring options. A series of experiments were performed on large, two-stroke and small, four-stroke diesel engines. Tests under normal operating conditions developed a detailed understanding of typical AE generation in terms of both the source mechanisms and the characteristics of the resulting activity. This was supplemented by specific tests to investigate possible AE generation at the ring-pack/liner interface. For instance, for the small engines measures were taken to remove known AE sources in order to accentuate any activity originating at the interface whilst for the large engines the interfacial conditions were purposely deteriorated through the removal of the lubricating oil supply to one cylinder. Interpretation of the results was based mainly upon comparisons with published work encompassing both the expected ring-pack behaviour and AE generation from tribological processes. This provided a strong indication that the source of the ring-pack/liner AE activity was the boundary frictional losses. The ability to monitor this process may be of significant benefit to engine operators as it enhances the diagnostic information currently available and may be incorporated into predictive maintenance strategies. A further diagnostic technique considered was the possibility of using AE parameters combined with information of crankshaft speed fluctuations to evaluate engine balance and identify underperforming cylinders.EU Competitive and Sustainable Growth Programme, Project no: GRD2-2001-5001

The detection of adhesive wear on cylinder liners for slow speed diesel engine through tribology, temperature, eddy current and acoustic emission measurement and analysis

PhD ThesisThe research concerns the condition monitoring of cylinder liner of large bore diesel engines using various methodologies to identify the onset of scuffing. The reasons of scuffing, improved designs and operational processes to prevent its occurrence were discussed. The research focused on modeling the normal condition of the cylinder liner with sufficient lubrication and detecting the precursor of scuffing by reducing the lubrication. The four detection systems used on the test facilities and field tests of the cylinder liners used tribology, temperature sensor, eddy current sensor and acoustic emission sensor. Experimental assessment of eddy current sensor was conducted for insufficient lubricating oil conditions for different cylinder liner wall pressures using a specially designed test facility. Field tests of temperature sensor and eddy current sensor were carried out on a 800mm bore worn cylinder liner of a container ship in service. Field test of acoustic emission sensor was carried out on a high speed automobile engine. Scuffing detection by temperature sensing should be considered as the last safety barrier, as it registers the after effect of scuffing and solely depends on the localized condition and the material’s thermal status. Mounting eddy current sensors are considered intrusive. Four sensors per cylinder are needed, which are prone to damage by the rings when the liner wears out. Additionally, the sensors measure only small section of the rings and their lubrication condition. Acoustic emission analysis effectively detects onset of scuffing on the cylinder liners and the rings. Initial findings from the lab and the field test on a four stroke engine confirmed this. However, more field tests under various loading condition on a slow speed engine is needed to understand the various event alignment and the non-routine detection, such as scuffing. They can be coupled with thermocouples to serve as a secondary protection

THE INVESTIGATION INTO THE CONDITION MONITORING OF TRIBOLOGICAL BEHAVIOUR BETWEEN PISTON RING AND CYLINDER LINER USING ACOUSTIC EMISSIONS

To improve engine operational performance and reliability, this study focuses on the investigation into the behaviour of tribological conjunction between the ring - liner based on a comprehensive analysis of non-intrusive acoustic emission (AE) measurement. Particularly, the study will provide more knowledge of using AE for online monitoring and diagnosing the performances of the conjunction. To fulfil this study, it integrates analytical predictions of the theoretical modelling for the AE generation mechanism with extensive experimental evaluations. Moreover, effective signal processing techniques are implemented with a combination of the model based AE predictions to extract the weak and nonstationary AE contents that correlate more with the tribological behaviour. Based on conventional tribological models, tribological AE is modelled to be due to two main dynamic effects: asperity-asperity collision (AAC) and fluid-asperity interaction (FAI), which allows measured AE signals from the tribological conjunction to be explained under different scenarios, especially under abnormal behaviours. FAI induced AE is more correlated with lubricants and velocity. It presents mainly in the middle of engine strokes but is much weaker and severely interfered with AEs from not only valve landings, combustion and fuel injection shocks but also the effect of considerable AACs due to direct contacts and solid particles in oils. To extract weak AEs for accurately diagnosing the tribological behaviours, wavelet transform analysis is applied to AE signals with three novel schemes: 1) hard threshold based wavelet coefficients selection in which the threshold value and wavelet analysis parameters are determined using a modified velocity of piston motion which has high dependence on the AE characteristics predicted by the two models; 2) Adaptive threshold wavelet coefficients selection in which the threshold is gradually updated to minimise the distance between the AE envelopes and the predicted dependence; and 3) wavelet packet transform (WPT) analysis is carried out by an optimised Daubechies wavelet through a novel approach based on minimising the time and frequency overlaps in WPT spectrum. Based on these optimal analyses, the local envelope amplitude (LEA) and the average residual wavelet coefficient (ARWC) are developed from AE signals as novel indicators to reflect the tribological behaviours.\ud Both the hard threshold based LEA and wavelet packet transform LEA values allow two different new lubricants to be diagnosed in accordance with model predictions whereas they produce less consistent results in differentiating the used oil under several operating conditions. Nevertheless, ARWC can separate the used oil successfully in that it can highlight the AAC effects of particle collisions in used oils. Similarly, LEA shows little impacts of two alternative fuels on the tribological behaviours. However, ARWC shows significantly higher amplitudes in several operating conditions when more particles can be produced due to unstable and incomplete combustions of both the biodiesel and FT diesel, compared with pure diesel, indicating they can cause light wear

A review of physics-based models in prognostics: application to gears and bearings of rotating machinery

Health condition monitoring for rotating machinery has been developed for many years due to its potential to reduce the cost of the maintenance operations and increase availability. Covering aspects include sensors, signal processing, health assessment and decision-making. This article focuses on prognostics based on physics-based models. While the majority of the research in health condition monitoring focuses on data-driven techniques, physics-based techniques are particularly important if accuracy is a critical factor and testing is restricted. Moreover, the benefits of both approaches can be combined when data-driven and physics-based techniques are integrated. This article reviews the concept of physics-based models for prognostics. An overview of common failure modes of rotating machinery is provided along with the most relevant degradation mechanisms. The models available to represent these degradation mechanisms and their application for prognostics are discussed. Models that have not been applied to health condition monitoring, for example, wear due to metal–metal contact in hydrodynamic bearings, are also included due to its potential for health condition monitoring. The main contribution of this article is the identification of potential physics-based models for prognostics in rotating machinery