Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

Statistical Monitoring of Dynamic Multivariate Processes: Part II: Identifying Fault Magnitude and Signature

This paper builds on work presented in the first paper, Part 1 [1] and is of equal significance. The paper proposes a novel compensation method to preserve the integrity of step-fault signatures prevalent in various processes that can be masked during the removal of both auto- and cross correlation. Using industrial data, the paper demonstrates the benefit of the proposed method, which is applicable to chemical, electrical, and mechanical process monitoring. This paper, (and Part 1 [1]), has led to further work supported by EPSRC grant GR/S84354/01 involving kernel PCA methods.

An Investigation into the Link between UK Credit Union Characterisitics, Location and their Success

The unique characteristics of credit unions reduces the information asymmetry that is prevalent in credit making decisions, enabling them to provide loans where other financial institutions cannot. This makes them a potential tool in the fight against financial exclusion. Yet, the UK credit union movement is not regarded as being successful, even though there is evidence of much financial exclusion. This study is cross sectional in form, and evaluates characteristics that may contribute to the success of the UK credit union movement at national and regional level, in 2000. The findings are used to consider the impact of recent regulatory changes on the movement. The key findings are that there is a significant relationship between the success of a credit union, its size and the deprivation of the ward from which it sources its members. More specifically, larger credit unions and those located in more affluent wards, are more successful. Affiliation to the Irish League of Credit Unions and having a common bond of occupation, are also found to be contributing factors to credit union success. These results are taken as providing support for the recent changes implemented by the Financial Services Authority (FSA), which is likely to result in the emergence of larger credit unions (through mergers), run by appropriately qualified persons, serving a more mixed-income membership base. It is, however, noted that the history of the UK movement is one of missed opportunities and only time will tell whether credit unions have the wherewithal to accept current opportunities.

Changes in functional behavior of 93 % Pb(Mg1/3Nb2/3)O-3-7 % PbTiO3 thin films induced by ac electric fields

The dielectric properties of Au/[93%Pb(Mg1/3Nb2/3)O-3-7%PbTiO3] (PMN-PT)/(La0.5Sr0.5)CoO3/MgO thin-film capacitor heterostructures, made using pulsed laser deposition, have been investigated, with particular emphasis on the changes in response associated with increasing the magnitude of the ac measuring field. It was found that increasing the ac field caused a change in the frequency spectrum of relaxators, increasing the speed of response of "slow" relaxators, with an associated decrease in the freezing temperature (T-f) of the relaxor system; in addition, other characteristic parameters relating to polar relaxation (activation energy E-a and attempt frequency 1/tau(0)), described by fitting of the dielectric response to a Vogel-Fulcher expression, were found to change continuously as ac field levels were increased.

Dynamics of electric fields driving the laser acceleration of multi-MeV protons

The acceleration of multi-MeV protons from the rear surface of thin solid foils irradiated by an intense (similar to 10(18) W/cm(2)) and short (similar to 1.5 ps) laser pulse has been investigated using transverse proton probing. The structure of the electric field driving the expansion of the proton beam has been resolved with high spatial and temporal resolution. The main features of the experimental observations, namely, an initial intense sheath field and a late time field peaking at the beam front, are consistent with the results from particle-in-cell and fluid simulations of thin plasma expansion into a vacuum.