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.

Distinguishing between similar tubular objects using pulse reflectometry: a study of trumpet and cornet leadpipes

Acoustic pulse reflectometry is used to reconstruct the internal bore profile of trumpet and cornet leadpipe. The method distinguishes between radii differences as small as 0.03 mm, and has since been used by various UK-based brass instrument manufacturers as a diagnostic tool to detect defects that are significant enough to acoustically alter performance.

Three primary kinetic characteristics observed in a pulse-response TAP experiment

The state-by-state transient screening approach based on a pulse-response thin-zone TAP experiment is further developed whereby single-pulse kinetic tests are treated as small perturbations to catalyst compositions and analyzed using integral method of moments. Results on three primary kinetic characteristics, termed basic kinetic coefficients, are presented. These three coefficients were introduced as main observables from experimentally measured TAP-responses in a kinetic-model-free manner. Each was analytically determined from moments of responses with no assumption about the detailed kinetic model. In this paper, the inverse question of how well these coefficients represent the time evolution of the observed responses is addressed. Sets of three basic kinetic coefficients are calculated from model and experimental responses and these calculated values are used to generate 3-coefficient curves in a kinetic-model-free manner. The comparison of these 3-coefficient curves with original responses shows that three basic kinetic coefficients can be sufficient to describe the observed kinetics of exit flow time dependencies with no assumption regarding the detailed kinetic model.

Effect of a COL1A1 Sp1 Binding Site Polymorphism on Arterial Pulse Wave Velocity: An Index of Compliance.

Reduced arterial compliance precedes changes in blood pressure, which may be mediated through alterations in vessel wall matrix composition. We investigated the effect of the collagen type I-1 gene (COL1A1) +2046G>T polymorphism on arterial compliance in healthy individuals. We recruited 489 subjects (251 men and 238 women; mean age, 22.6±1.6 years). COL1A1 genotypes were determined using polymerase chain reaction and digestion by restriction enzyme Bal1. Arterial pulse wave velocities were measured in 3 segments, aortoiliac (PWVA), aortoradial (PWVB), and aorto-dorsalis-pedis (PWVF), as an index of compliance using a noninvasive optical method. Data were available for 455 subjects. The sample was in Hardy-Weinberg equilibrium with genotype distributions and allele frequencies that were not significantly different from those reported previously. The T allele frequency was 0.22 (95% confidence interval, 0.19 to 0.24). Two hundred eighty-three (62.2%) subjects were genotype GG, 148 (35.5%) subjects were genotype GT, and 24 (5.3%) subjects were genotype TT. A comparison of GG homozygotes with GT and TT individuals demonstrated a statistically significant association with arterial compliance: PWVF 4.92±0.03 versus 5.06±0.05 m/s (ANOVA, P=0.009), PWVB 4.20±0.03 versus 4.32±0.04 m/s (ANOVA, P=0.036), and PWVA 3.07±0.03 versus 3.15±0.03 m/s (ANOVA, P=0.045). The effects of genotype were independent of age, gender, smoking, mean arterial pressure, body mass index, family history of hypertension, and activity scores. We report an association between the COL1A1 gene polymorphism and arterial compliance. Alterations in arterial collagen type 1A deposition may play a role in the regulation of arterial compliance