Bayesian models for the determination of resonant frequencies in a DI diesel engine

A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information.

Estimating the loading condition of a diesel engine using instantaneous angular speed analysis

Continuing monitoring of diesel engine performance is critical for early detection of fault developments in the engine before they materialize and become a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few non intrusive condition monitoring techniques that can be utilized for such tasks. In this experimental study, IAS analysis was employed to estimate the loading condition of a 4-stroke 4-cylinder diesel engine in a laboratory condition. It was shown that IAS analysis can provide useful information about engine speed variation caused by the changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectrum directly associated with the engine firing frequency (at twice the mean shaft revolution speed) can be utilized to estimate the engine loading condition regardless of whether the engine is operating at normal running conditions or in a simulated faulty injector case. The amplitude of this order component follows a clear exponential curve as the loading condition changes. A mathematical relationship was established for the estimation of the engine power output based on the amplitude of the major order component of the measured IAS spectrum.

Estimating the loading condition of a diesel engine using instantaneous angular speed analysis

Continuing monitoring of diesel engine performance is critical for early detection of fault developments in the engine before they materialize and become a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few non intrusive condition monitoring techniques that can be utilized for such tasks. In this experimental study, IAS analysis was employed to estimate the loading condition of a 4-stroke 4-cylinder diesel engine in a laboratory condition. It was shown that IAS analysis can provide useful information about engine speed variation caused by the changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectrum directly associated with the engine firing frequency (at twice the mean shaft revolution speed) can be utilized to estimate the engine loading condition regardless of whether the engine is operating at normal running conditions or in a simulated faulty injector case. The amplitude of this order component follows a clear exponential curve as the loading condition changes. A mathematical relationship was established for the estimation of the engine power output based on the amplitude of the major order component of the measured IAS spectrum.

Volatile properties of particles emitted by compressed natural gas and diesel buses during steady state and transient driving modes

Volatile properties of particle emissions from four compressed natural gas (CNG) and four diesel buses were investigated under steady state and transient driving modes on a chassis dynamometer. The exhaust was diluted utilising a full-flow continuous volume sampling system and passed through a thermodenuder at controlled temperature. Particle number concentration and size distribution were measured with a condensation particle counter and a scanning mobility particle sizer, respectively. We show that, while almost all the particles emitted by the CNG buses were in the nanoparticle size range, at least 85% and 98% were removed at 100ºC and 250ºC, respectively. Closer analysis of the volatility of particles emitted during transient cycles showed that volatilisation began at around 40°C with the majority occurring by 80°C. Particles produced during hard acceleration from rest exhibited lower volatility than that produced during other times of the cycle. Based on our results and the observation of ash deposits on the walls of the tailpipes, we suggest that these non-volatile particles were composed mostly of ash from lubricating oil. Heating the diesel bus emissions to 100ºC removed ultrafine particle numbers by 69% to 82% when a nucleation mode was present and just 18% when it was not.

Condition monitoring and diagnosis of injector faults in a diesel engine using in-cylinder pressure and acoustic emission techniques

Failing injectors are one of the most common faults in diesel engines. The severity of these faults could have serious effects on diesel engine operations such as engine misfire, knocking, insufficient power output or even cause a complete engine breakdown. It is thus essential to prevent such faults from occurring by monitoring the condition of these injectors. In this paper, the authors present the results of an experimental investigation on identifying the signal characteristics of a simulated incipient injector fault in a diesel engine using both in-cylinder pressure and acoustic emission (AE) techniques. A time waveform event driven synchronous averaging technique was used to minimize or eliminate the effect of engine speed variation and amplitude fluctuation. It was found that AE is an effective method to detect the simulated injector fault in both time (crank angle) and frequency (order) domains. It was also shown that the time domain in-cylinder pressure signal is a poor indicator for condition monitoring and diagnosis of the simulated injector fault due to the small effect of the simulated fault on the engine combustion process. Nevertheless, good correlations between the simulated injector fault and the lower order components of the enveloped in-cylinder pressure spectrum were found at various engine loading conditions.

A physico-chemical characterisation of particulate emissions from a compression ignition engine : the influence of biodiesel feedstock

This study undertook a physico-chemical characterisation of particle emissions from a single compression ignition engine operated at one test mode with 3 biodiesel fuels made from 3 different feedstocks (i.e. soy, tallow and canola) at 4 different blend percentages (20%, 40%, 60% and 80%) to gain insights into their particle-related health effects. Particle physical properties were inferred by measuring particle number size distributions both with and without heating within a thermodenuder (TD) and also by measuring particulate matter (PM) emission factors with an aerodynamic diameter less than 10 μm (PM10). The chemical properties of particulates were investigated by measuring particle and vapour phase Polycyclic Aromatic Hydrocarbons (PAHs) and also Reactive Oxygen Species (ROS) concentrations. The particle number size distributions showed strong dependency on feedstock and blend percentage with some fuel types showing increased particle number emissions, whilst others showed particle number reductions. In addition, the median particle diameter decreased as the blend percentage was increased. Particle and vapour phase PAHs were generally reduced with biodiesel, with the results being relatively independent of the blend percentage. The ROS concentrations increased monotonically with biodiesel blend percentage, but did not exhibit strong feedstock variability. Furthermore, the ROS concentrations correlated quite well with the organic volume percentage of particles – a quantity which increased with increasing blend percentage. At higher blend percentages, the particle surface area was significantly reduced, but the particles were internally mixed with a greater organic volume percentage (containing ROS) which has implications for using surface area as a regulatory metric for diesel particulate matter (DPM) emissions.

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.

Characterisation and source identification of selected pollutants in house dust

House dust is a heterogeneous matrix, which contains a number of biological materials and particulate matter gathered from several sources. It is the accumulation of a number of semi-volatile and non-volatile contaminants. The contaminants are trapped and preserved. Therefore, house dust can be viewed as an archive of both the indoor and outdoor air pollution. There is evidence to show that on average, people tend to stay indoors most of the time and this increases exposure to house dust. The aims of this investigation were to: " assess the levels of Polycyclic Aromatic Hydrocarbons (PAHs), elements and pesticides in the indoor environment of the Brisbane area; " identify and characterise the possible sources of elemental constituents (inorganic elements), PAHs and pesticides by means of Positive Matrix Factorisation (PMF); and " establish the correlations between the levels of indoor air pollutants (PAHs, elements and pesticides) with the external and internal characteristics or attributes of the buildings and indoor activities by means of multivariate data analysis techniques. The dust samples were collected during the period of 2005-2007 from homes located in different suburbs of Brisbane, Ipswich and Toowoomba, in South East Queensland, Australia. A vacuum cleaner fitted with a paper bag was used as a sampler for collecting the house dust. A survey questionnaire was filled by the house residents which contained information about the indoor and outdoor characteristics of their residences. House dust samples were analysed for three different pollutants: Pesticides, Elements and PAHs. The analyses were carried-out for samples of particle size less than 250 µm. The chemical analyses for both pesticides and PAHs were performed using a Gas Chromatography Mass Spectrometry (GC-MS), while elemental analysis was carried-out by using Inductively-Coupled Plasma-Mass Spectroscopy (ICP-MS). The data was subjected to multivariate data analysis techniques such as multi-criteria decision-making procedures, Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE), coupled with Geometrical Analysis for Interactive Aid (GAIA) in order to rank the samples and to examine data display. This study showed that compared to the results from previous works, which were carried-out in Australia and overseas, the concentrations of pollutants in house dusts in Brisbane and the surrounding areas were relatively very high. The results of this work also showed significant correlations between some of the physical parameters (types of building material, floor level, distance from industrial areas and major road, and smoking) and the concentrations of pollutants. Types of building materials and the age of houses were found to be two of the primary factors that affect the concentrations of pesticides and elements in house dust. The concentrations of these two types of pollutant appear to be higher in old houses (timber houses) than in the brick ones. In contrast, the concentrations of PAHs were noticed to be higher in brick houses than in the timber ones. Other factors such as floor level, and distance from the main street and industrial area, also affected the concentrations of pollutants in the house dust samples. To apportion the sources and to understand mechanisms of pollutants, Positive Matrix Factorisation (PMF) receptor model was applied. The results showed that there were significant correlations between the degree of concentration of contaminants in house dust and the physical characteristics of houses, such as the age and the type of the house, the distance from the main road and industrial areas, and smoking. Sources of pollutants were identified. For PAHs, the sources were cooking activities, vehicle emissions, smoking, oil fumes, natural gas combustion and traces of diesel exhaust emissions; for pesticides the sources were application of pesticides for controlling termites in buildings and fences, treating indoor furniture and in gardens for controlling pests attacking horticultural and ornamental plants; for elements the sources were soil, cooking, smoking, paints, pesticides, combustion of motor fuels, residual fuel oil, motor vehicle emissions, wearing down of brake linings and industrial activities.

Gaseous and particle emissions from an ethanol fumigated compression ignition engine

A 4-cylinder Ford 2701C test engine was used in this study to explore the impact of ethanol fumigation on gaseous and particle emission concentrations. The fumigation technique delivered vaporised ethanol into the intake manifold of the engine, using an injector, a pump and pressure regulator, a heat exchanger for vaporising ethanol and a separate fuel tank and lines. Gaseous (Nitric oxide (NO), Carbon monoxide (CO) and hydrocarbons (HC)) and particulate emissions (particle mass (PM2.5) and particle number) testing was conducted at intermediate speed (1700 rpm) using 4 load settings with ethanol substitution percentages ranging from 10-40 % (by energy). With ethanol fumigation, NO and PM2.5 emissions were reduced, whereas CO and HC emissions increased considerably and particle number emissions increased at most test settings. It was found that ethanol fumigation reduced the excess air factor for the engine and this led to increased emissions of CO and HC, but decreased emissions of NO. PM2.5 emissions were reduced with ethanol fumigation, as ethanol has a very low “sooting” tendency. This is due to the higher hydrogen-to-carbon ratio of this fuel, and also because ethanol does not contain aromatics, both of which are known soot precursors. The use of a diesel oxidation catalyst (as an after-treatment device) is recommended to achieve a reduction in the four pollutants that are currently regulated for compression ignition engines. The increase in particle number emissions with ethanol fumigation was due to the formation of volatile (organic) particles; consequently, using a diesel oxidation catalyst will also assist in reducing particle number emissions.

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.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Physicochemical characterization of particulate emissions from a compression ignition engine employing two injection technologies and three fuels

Alternative fuels and injection technologies are a necessary component of particulate emission reduction strategies for compression ignition engines. Consequently, this study undertakes a physicochemical characterization of diesel particulate matter (DPM) for engines equipped with alternative injection technologies (direct injection and common rail) and alternative fuels (ultra low sulfur diesel, a 20% biodiesel blend, and a synthetic diesel). Particle physical properties were addressed by measuring particle number size distributions, and particle chemical properties were addressed by measuring polycyclic aromatic hydrocarbons (PAHs) and reactive oxygen species (ROS). Particle volatility was determined by passing the polydisperse size distribution through a thermodenuder set to 300 °C. The results from this study, conducted over a four point test cycle, showed that both fuel type and injection technology have an impact on particle emissions, but injection technology was the more important factor. Significant particle number emission (54%–84%) reductions were achieved at half load operation (1% increase–43% decrease at full load) with the common rail injection system; however, the particles had a significantly higher PAH fraction (by a factor of 2 to 4) and ROS concentrations (by a factor of 6 to 16) both expressed on a test-cycle averaged basis. The results of this study have significant implications for the health effects of DPM emissions from both direct injection and common rail engines utilizing various alternative fuels.

Pyrolysis decomposition of mahogony seeds (Swietenia macrophylla) for alternative fuel oil

A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from Mahogany seeds. The major components of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collectors. The Mahogany seed in particle form is pyrolysed in an externally heated 10 cm diameter and 36 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 450oC to 600oC. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. A maximum liquid yield of 54wt% of biomass feed is obtained with particle size of 1.18 mm at a reactor bed temperature of 5500C with a running time of 90 minutes. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 39.9 MJ/kg which is higher than other biomass derived pyrolysis oils.

Respiratory health effects of diesel particulate matter

Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.

Production of liquid fuel and activated carbon from mahogany seed by using pyrolysis technology

The renovation of biomass waste in the form of Mahogany seed waste into bio-fuel as well as activated carbon by fixed bed pyrolysis reactor has been taken into consideration in this study. The mahogany seed in particle form is pyrolyzed in an enormously heated fixed bed reactor with nitrogen as the carrier gas. The reactor is heated from 4000C to 6000C using a external heater in which rice husk and charcoal are used as the heater biomass fuel. Reactor bed temperature, running time and feed particle size have been varied to get the optimum operating conditions of the system. The parameters are found to influence the product yields to a large extent. A maximum liquid and char yield are 49 wt. % and 35 wt. % respectively obtained at a reactor bed temperature 5000C when the running time is 90 minutes. Acquired pyrolyzed oil at these optimal process conditions were analyzed for some of their properties as an alternative fuel. The oil possesses comparable flame temperature, favorable flash point and reasonable viscosity along with somewhat higher density. The kinematic viscosity of the derived fuel is 3.8 cSt and density is 1525 kg/m3. The higher calorific value is found 32.4 MJ/kg which is significantly higher than other biomass derived fuel. Moderate adsorption capacity of the prepared activated carbon in case of methyl blue & tea water was also revealed.