Enhancing acoustic emission signals from multi-cylinder diesel engine

This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.

Separation of acoustic emission signals from small size multi-cylinder diesel engine

This paper presents techniques which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outline, including time-frequency analysis and selection of optimum frequency band.The results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals and the effects of changing parameter values are also outlined. The results on separation of RMS signals show thsi technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events within the combustion process of multi-cylinder diesel engines.

Diesel engine problems, acoustic emission signals and simulated misfire faults

This paper discusses commonly encountered diesel engine problems and the underlying combustion related faults. Also discussed are the methods used in previous studies to simulate diesel engine faults and the initial results of an experimental simulation of a common combustion related diesel engine fault, namely diesel engine misfire. This experimental fault simulation represents the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank-angle encoder and top-dead centre signals. Using these signals, it was possible to characterise the diesel engine in-cylinder pressure profiles and the effect of different combustion conditions on both vibration and acoustic emission signals.

Detection of excessive diesel engine piston slap using acoustic emission signals

This paper presents a study whereby a series of tests was undertaken using a naturally aspirated 4 cylinder, 2.216 litre, Perkins Diesel engine fitted with a piston having an undersized skirt. This experimental simulation resulted in engine running conditions that included abnormally high levels of piston slap occurring in one of the cylinders. The detectability of the resultant Diesel engine piston slap was investigated using acoustic emission signals. Data corresponding to both normal and piston slap engine running conditions was captured using acoustic emission transducers along with both; in-cylinder pressure and top-dead centre reference signals. Using these signals it was possible to demonstrate that the increased piston slap running conditions were distinguishable by monitoring the piston slap events occurring near the piston mid-stroke positions. However, when monitoring the piston slap events occurring near the TDC/BDC piston stroke positions, the normal and excessive piston slap engine running condition were not clearly distinguishable.

Parametric analysis of acoustic emission signals for evaluating damage in composites using a PVDF film sensor

With the increased utilization of advanced composites in strategic industries, the concept of Structural Health Monitoring (SHM) with its inherent advantages is gaining ground over the conventional methods of NDE and NDI. The most attractive feature of this concept is on-line evaluation using embedded sensors. Consequently, development of methodologies with identification of appropriate sensors such as PVDF films becomes the key for exploiting the new concept. And, of the methods used for on-line evaluation acoustic emission has been most effective. Thus, Acoustic Emission (AE) generated during static tensile loading of glass fiber reinforced plastic composites was monitored using a Polyvinylidene fluoride (PVDF) film sensor. The frequency response of the film sensor was obtained with pencil lead breakage tests to choose the appropriate band of operation. The specimen considered for the experiments were chosen to characterize the differences in the operation of the failure mechanisms through AE parametric analysis. The results of the investigations can be characterized using AE parameter indicating that a PVDF film sensor was effective as an AE sensor used in structural health monitoring on-line.

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

Experimentally induced diesel engine injector faults and some preliminary acoustic emission signal observations

Diesel engine fuel injector faults can lead to reduced power, increased fuel consumption and greater exhaust emission levels and if left unchecked, can eventually lead to premature engine failure. This paper provides an overview of the Diesel, or compression ignition combustion process, and of the two basic fuel injector nozzle designs used in Diesel engines, namely, the pintle-type and hole-type nozzles. Also described are some common faults associated with these two types of fuel injector nozzles and the techniques previously used to experimentally simulate these faults. This paper also presents a recent experimental campaign undertaken using two different diesel engines whereby various fuel injector nozzle faults were induced into the engines. The first series of tests was undertaken using a turbo-charged 5.9 litre; Cummins Diesel engine whist the second series of tests was undertaken using a naturally aspirated 4 cylinder, 2.216 litre, Perkins Diesel engine. Data corresponding to different injector fault conditions was captured using in-cylinder pressure, and acoustic emission transducers along with both crank-angle encoder and top-dead centre reference signals. Using averaged in-cylinder pressure signals, it was possible to qualify the severity of the faults whilst averaged acoustic emission signals were in turn, used as the basis for wavelets decomposition. Initial observations from this signal decomposition are also presented and discussed.

Diesel knock combustion and its detection using acoustic emission

This paper presents an experimental investigation into the detection of excessive Diesel knock using acoustic emission signals. Three different dual-fuel Diesel engine operating regimes were induced into a compression ignition (Diesel) engine operating on both straight Diesel fuel and two different mixtures of fumigated ethanol and Diesel. The experimentally induced engine operating regimes were; normal, or Diesel only operation, acceptable dual-fuel operation and dual-fuel operation with excessive Diesel knock. During the excessive Diesel knock operating regime, high rates of ethanol substitution induced potentially damaging levels of Diesel knock. Acoustic emission data was captured along with cylinder pressure, crank-angle encoder, and top-dead centre signals for the different engine operating regimes. Using these signals, it was found that acoustic emission signals clearly distinguished between the two acceptable operating regimes and the operating regime experiencing excessive Diesel knock. It was also found that acoustic emission sensor position is critical. The acoustic emission sensor positioned on the block of the engine clearly related information concerning the level of Diesel knock occurring in the engine whist the sensor positioned on the head of the engine gave no indication concerning Diesel knock severity levels.

Studies on indentation fracture toughness on ceramic and ceramic composite using acoustic emission technique

This paper is aimed at investigating the acoustic emission activities during indentation toughness tests on an alumina based wear resistant ceramic and 25 wt% silicon carbide whisker (SIC,) reinforced alumina composite. It has been shown that the emitted acoustic emission signals characterize the crack growth during loading. and unloading cycles in an indentation test. The acoustic emission results indicate that in the case of the composite the amount of crack growth during unloading is higher than that of loading, while the reverse is true in case of the wear resistant ceramics. Acoustic emission activity observed in wear resistant ceramic is less than that in the case of composite. An attempt has been made to correlate the acoustic emission signals with crack growth during indentation test.

General framework for acoustic emission during plastic deformation

Despite the long history, so far there is no general theoretical framework for calculating the acoustic emission spectrum accompanying any plastic deformation. We set up a discrete wave equation with plastic strain rate as a source term and include the Rayleigh-dissipation function to represent dissipation accompanying acoustic emission. We devise a method of bridging the widely separated time scales of plastic deformation and elastic degrees of freedom. While this equation is applicable to any type of plastic deformation, it should be supplemented by evolution equations for the dislocation microstructure for calculating the plastic strain rate. The efficacy of the framework is illustrated by considering three distinct cases of plastic deformation. The first one is the acoustic emission during a typical continuous yield exhibiting a smooth stress-strain curve. We first construct an appropriate set of evolution equations for two types of dislocation densities and then show that the shape of the model stress-strain curve and accompanying acoustic emission spectrum match very well with experimental results. The second and the third are the more complex cases of the Portevin-Le Chatelier bands and the Luders band. These two cases are dealt with in the context of the Ananthakrishna model since the model predicts the three types of the Portevin-Le Chatelier bands and also Luders-like bands. Our results show that for the type-C bands where the serration amplitude is large, the acoustic emission spectrum consists of well-separated bursts of acoustic emission. At higher strain rates of hopping type-B bands, the burst-type acoustic emission spectrum tends to overlap, forming a nearly continuous background with some sharp acoustic emission bursts. The latter can be identified with the nucleation of new bands. The acoustic emission spectrum associated with the continuously propagating type-A band is continuous. These predictions are consistent with experimental results. More importantly, our study shows that the low-amplitude continuous acoustic emission spectrum seen in both the type-B and type-A band regimes is directly correlated to small-amplitude serrations induced by propagating bands. The acoustic emission spectrum of the Luders-like band matches with recent experiments as well. In all of these cases, acoustic emission signals are burstlike, reflecting the intermittent character of dislocation-mediated plastic flow.

In-process grinding monitoring by acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS.

Detection of cracks in scratching tests in ceramic materials through acoustic emission

The mechanisms of material removal and the interactions among scratches performed in ceramic materials were investigated using acoustic emission signals, and scanning electron microscopy, in scratching experiments. Several testing conditions were used to produce different types of removing mechanism on a glass as well as on a polycrystalline alumina sample composed by heterogeneous grain size. It is known that the material removing process on a polycrystalline ceramic involves intergranular microfracture and grain dislodgement, unlike the chipping produced by the extension of lateral cracks in non-granular materials, such as glass. Distinct settings for velocities, loads, and two types of diamond indenter were tested. The material removal was carried out by three different methods of scratching: single passes, repeated overlapping passes, and parallel scratches. As a general result, there was a clear relationship between the acoustic emission signals and the damage intensity occurred in the material removal. More specifically, there were differences in the acoustic emission signal levels in the scratches made on the alumina and on the glass owing to the material removal mechanisms associated with the structure of these materials. A gradual increase in the acoustic emission levels was observed when the number of repeated passes was increased as a result of the damage accumulation process followed by severe material removal. It was also noticed that the acoustic emission signals were capable of reflecting the interactions between two parallel scratches.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

In-process grinding monitoring through acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS. Copyright © 2006 by ABCM.