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.

Is perception of upper body orientation based on the inertia tensor? Normogravity versus microgravity conditions

During lateral leg raising, a synergistic inclination of the supporting leg and trunk in the opposite direction to the leg movement is performed in order to preserve equilibrium. As first hypothesized by Pagano and Turvey (J Exp Psychol Hum Percept Perform, 1995, 21:1070-1087), the perception of limb orientation could be based on the orientation of the limb's inertia tensor. The purpose of this study was thus to explore whether the final upper body orientation (trunk inclination relative to vertical) depends on changes in the trunk inertia tensor. We imposed a loading condition, with total mass of 4 kg added to the subject's trunk in either a symmetrical or asymmetrical configuration. This changed the orientation of the trunk inertia tensor while keeping the total trunk mass constant. In order to separate any effects of the inertia tensor from the effects of gravitational torque, the experiment was carried out in normo- and microgravity. The results indicated that in normogravity the same final upper body orientation was maintained irrespective of the loading condition. In microgravity, regardless of loading conditions the same (but different from the normogravity) orientation of the upper body was achieved through different joint organizations: two joints (the hip and ankle joints of the supporting leg) in the asymmetrical loading condition, and one (hip) in the symmetrical loading condition. In order to determine whether the different orientations of the inertia tensor were perceived during the movement, the interjoint coordination was quantified by performing a principal components analysis (PCA) on the supporting and moving hips and on the supporting ankle joints. It was expected that different loading conditions would modify the principal component of the PCA. In normogravity, asymmetrical loading decreased the coupling between joints, while in microgravity a strong coupling was preserved whatever the loading condition. It was concluded that the trunk inertia tensor did not play a role during the lateral leg raising task because in spite of the absence of gravitational torque the final upper body orientation and the interjoint coupling were not influenced.

Differences In Metabolic Profile In the Testes of Streptozotocin Induced Diabetes Mellitus Mice As Detected By 1H NMR

Contrary to the traditional view, recent studies suggest that diabetes mellitus has an adverse influence on male reproductive function. Our aim was to determine the affect of diabetes on the testicular environment by identifying and then assessing perturbations in small molecule metabolites. Testes were obtained from control and streptozotocin induced diabetic C57BL/6 mice, two, four and eight weeks post treatment. Diabetic status was confirmed by HbA1c, non fasting blood glucose, physiological condition and body weight. Protein free, low molecular weight, water soluble extracts were assessed using 1H NMR spectroscopy. Principal Component Analysis of the derived profiles was used to classify any variations and specific metabolites were identified based on their spectral pattern. Characteristic metabolite profiles were identified for control and diabetic animals with the most distinctive being from mice with the greatest physical deterioration and loss of bodyweight. Eight streptozotocin treated animals did not develop diabetes and displayed profiles similar to controls. Diabetic mice had decreases in creatine, choline and carnitine and increases in lactate, alanine and myo-inositol. Betaine levels were found to be increased in the majority of diabetic mice but decreased in two animals with severe loss of body weight and physical condition. The association between perturbations in a number of small molecule metabolites known to be influential in sperm function, with diabetic status and physiological condition, adds further impetus to the proposal that diabetes influences important spermatogenic pathways and mechanisms in a subtle and previously unrecognised manner.

A Holocene record of human induced and natural environmental change from Lake Forsyth (Te Wairewa), New Zealand

A 1.2 m sediment core from Lake Forsyth, Canterbury, New Zealand, records the development of the catchment/lake system over the last 7000 years, and its response to anthropogenic disturbance following European settlement c. 1840 AD. Pollen was used to reconstruct catchment vegetation history, while foraminifera, chironomids, Trichoptera, and the abundance of Pediastrum simplex colonies were used to infer past environmental conditions within the lake. The basal 30 cm of core records the transition of the Lake Forsyth Basin from a tidal embayment to a brackish coastal lake. Timing of closure of the lake mouth could not be accurately determined, but it appears that Lake Forsyth had stabilised as a slightly brackish, oligo mesotrophic shallow lake by about 500 years BP. Major deforestation occurred on Banks Peninsula between 1860 AD and 1890 AD. This deforestation is marked by the rapid decline in the main canopy trees (Prumnopitys taxifolia (matai) and Podocarpus totara/hallii (totara/mountain totara), an increase in charcoal, and the appearance of grasses. At around 1895 AD, pine appears in the record while a willow (Salix spp.) appears somewhat later. Redundancy analysis (RDA) of the pollen and aquatic species data revealed a significant relationship between regional vegetation and the abundance of aquatic taxa, with the percentage if disturbance pollen explaining most (14.8%) of the constrained variation in the aquatic species data. Principle components analysis (PCA) of aquatic species data revealed that the most significant period of rapid biological change in the lakes history corresponded to the main period of human disturbance in the catchment. Deforestation led to increased sediment and nutrient input into the lake which was accompanied by a major reduction in salinity. These changes are inferred from the appearance and proliferation of freshwater algae (Pediastrum simplex), an increase in abundance and diversity of chironomids, and the abundance of cases and remains from the larvae of the caddisfly, Oecetis unicolor. Eutrophication accompanied by increasing salinity of the lake is inferred from a significant peak and then decline of P. simplex, and a reduction in the abundance and diversity of aquatic invertebrates. The artificial opening of the lake to the Pacific Ocean, which began in the late 1800s, is the likely cause of the recent increase in salinity. An increase in salinity may have also encouraged blooms of the halotolerant and hepatotoxic cyanobacteria Nodularia spumigena.

Observation of fast hydrogen atoms formed by ion bombarding of surfaces

We report on the observation of fast hydrogen atoms in a capacitively coupled RF reactor by optical emission spectroscopy. For the analysis we use the prominent H-alpha emission line of atomic hydrogen in combination with other lines from molecular hydrogen and argon. Several chaxacteristic emission structures can be identified. One of these structures is related to fast hydrogen atoms traveling from the surface of the powered electrode to the plasma bulk. From the appearance time within the RF period we conclude that this feature originates from ion bombardment of the electrode surface. Measured pressure dependencies and a simple model for the ion dynamics support this assumption.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

Improved reliability in diagnosing faults using multivariate statistics

This paper analyses multivariate statistical techniques for identifying and isolating abnormal process behaviour. These techniques include contribution charts and variable reconstructions that relate to the application of principal component analysis (PCA). The analysis reveals firstly that contribution charts produce variable contributions which are linearly dependent and may lead to an incorrect diagnosis, if the number of principal components retained is close to the number of recorded process variables. The analysis secondly yields that variable reconstruction affects the geometry of the PCA decomposition. The paper further introduces an improved variable reconstruction method for identifying multiple sensor and process faults and for isolating their influence upon the recorded process variables. It is shown that this can accommodate the effect of reconstruction, i.e. changes in the covariance matrix of the sensor readings and correctly re-defining the PCA-based monitoring statistics and their confidence limits. (c) 2006 Elsevier Ltd. All rights reserved.

Factors influencing the distribution of native and introduced Gammarus spp. in Irish river systems

Populations of Gammarus duebeni celticus, previously the only amphipod species resident in the rivers of the Lough Neagh catchment, N. Ireland, have been subjected to invasion by G. pulex from the British mainland. Numerous previous studies have investigated the potential behavioural mechanisms, principally differential mutual predation, underlying the replacement of G. d. celticus by G. pulex in Irish waters, and the mutually exclusive distributions of these species in Britain and mainland Europe. However, the relative degree of influence of abiotic versus biotic factors in structuring these amphipod communities remains unresolved. This study used principal component analysis (PCA) to distinguish physico-chemical parameters that have significant roles in determining the current distribution of G. pulex relative to G. d. celticus in L. Neagh rivers. We show that the original domination of rivers by the native G. d, celticus has changed radically, with many sites in several rivers containing either both species or only G. pulex. G. pulex was more abundant than the G. d. celticus in sites with low dissolved oxygen levels. This was reflected in the macroinvertebrate assemblages associated with G. pulex in these sites, which tended to be those tolerant of low biological water quality. The present study thus emphasizes the importance of the habitat template, particularly water quality, for Gammarus spp. interactions. If rivers become increasingly stressed by organic pollution, it is probable the range expansion of G. pulex will continue. Because these two species are not ecological equivalents, the outcomes of G. pulex incursions into G. d. celticus sites may ultimately depend on the prevailing physico-chemical regimes in each site.

Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.

Responses of calves to acute stress: Individual consistency and relations between behavioral and physiological measures

The present study examined the consistency over time of individual differences in behavioral and physiological responsiveness of calves to intuitively alarming test situations as well as the relationships between behavioral and physiological measures. Twenty Holstein Friesian heifer calves were individually subjected to the same series of two behavioral and two hypothalamo-pituitary-adrenocortical (HPA) axis reactivity tests at 3, 13 and 26 weeks of age. Novel environment (open field, OF) and novel object (NO) tests involved measurement of behavioral, plasma cortisol and heart rate responses. Plasma ACTH and/or cortisol response profiles were determined after administration of exogenous CRH and ACTH, respectively, in the HPA axis reactivity tests. Principal component analysis (PCA) was used to condense correlated measures within ages into principal components reflecting independent dimensions underlying the calves' reactivity. Cortisol responses to the OF and NO tests were positively associated with the latency to contact and negatively related to the time spent in contact with the NO. Individual differences in scores of a principal component summarizing this pattern of inter-correlations, as well as differences in separate measures of adrenocortical and behavioral reactivity in the OF and NO tests proved highly consistent over time. The cardiac response to confinement in a start box prior to the OF test was positively associated with the cortisol responses to the OF and NO tests at 26 weeks of age. HPA axis reactivity to ACTH or CRH was unrelated to adrenocortical and behavioral responses to novelty. These findings strongly suggest that the responsiveness of calves was mediated by stable individual characteristics. Correlated adrenocortical and behavioral responses to novelty may reflect underlying fearfulness, defining the individual's susceptibility to the elicitation of fear. Other independent characteristics mediating reactivity may include activity or coping style (related to locomotion) and underlying sociality (associated with vocalization). (c) 2005 Elsevier Inc. All rights reserved.

Statistical-based monitoring of multivariate non-Gaussian systems

The monitoring of multivariate systems that exhibit non-Gaussian behavior is addressed. Existing work advocates the use of independent component analysis (ICA) to extract the underlying non-Gaussian data structure. Since some of the source signals may be Gaussian, the use of principal component analysis (PCA) is proposed to capture the Gaussian and non-Gaussian source signals. A subsequent application of ICA then allows the extraction of non-Gaussian components from the retained principal components (PCs). A further contribution is the utilization of a support vector data description to determine a confidence limit for the non-Gaussian components. Finally, a statistical test is developed for determining how many non-Gaussian components are encapsulated within the retained PCs, and associated monitoring statistics are defined. The utility of the proposed scheme is demonstrated by a simulation example, and the analysis of recorded data from an industrial melter.

Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

In this paper, a novel motion-tracking scheme using scale-invariant features is proposed for automatic cell motility analysis in gray-scale microscopic videos, particularly for the live-cell tracking in low-contrast differential interference contrast (DIC) microscopy. In the proposed approach, scale-invariant feature transform (SIFT) points around live cells in the microscopic image are detected, and a structure locality preservation (SLP) scheme using Laplacian Eigenmap is proposed to track the SIFT feature points along successive frames of low-contrast DIC videos. Experiments on low-contrast DIC microscopic videos of various live-cell lines shows that in comparison with principal component analysis (PCA) based SIFT tracking, the proposed Laplacian-SIFT can significantly reduce the error rate of SIFT feature tracking. With this enhancement, further experimental results demonstrate that the proposed scheme is a robust and accurate approach to tackling the challenge of live-cell tracking in DIC microscopy.

Metabolic profile changes in the testes of mice with streptozotocin-induced type 1 diabetes mellitus

Contrary to the traditional view, recent studies suggest that diabetes mellitus has an adverse influence on male reproductive function. Our aim was to determine the effect of diabetes on the testicular environment by identifying and then assessing perturbations in small molecule metabolites. Testes were obtained from control and streptozotocin-induced diabetic C57BL/6 mice, 2, 4 and 8 weeks post-treatment. Diabetic status was confirmed by glycated haemoglobin, non-fasting blood glucose, physiological condition and body weight. A novel extraction procedure was utilized to obtain protein free, low-molecular weight, water soluble extracts which were then assessed using H-1 nuclear magnetic resonance spectroscopy. Principal component analysis of the derived profiles was used to classify any variations, and specific metabolites were identified based on their spectral pattern. Characteristic metabolite profiles were identified for control and type 1 diabetic animals with the most distinctive being from mice with the largest physical deterioration and loss of body weight. Eight streptozotocin-treated animals did not develop diabetes and displayed profiles similar to controls. Diabetic mice had decreases in creatine, choline and carnitine and increases in lactate, alanine and myo-inositol. Betaine levels were found to be increased in the majority of diabetic mice but decreased in a few animals with severe loss of body weight and physical condition. The association between perturbations in a number of small molecule metabolites known to be influential in sperm function, with diabetic status and physiological condition, adds further impetus to the proposal that diabetes influences important spermatogenic pathways and mechanisms in a subtle and previously unrecognized manner.