The use of IGBT power modules in the automotive industry is becoming increasingly common as manufacturers develop more hybrid and all electric vehicles. In an industry such as this, the reliability of a component is critical and vehicle manufacturers have conducted much research into diagnostic and prognostic systems for internal combustion engines that run in real time on the vehicle to determine when components will fail. Power electronic components do not have similar prognostics available. The traditional use of power electronic modules has been in applications where their life or duty cycle is well defined, and accelerated life tests are carried out to determine a mean time to failure. This type of prognostics is not appropriate for the automotive industry because the operating cycle of the vehicle varies greatly, both in driving style, duty cycle and environment. A new type of prognostics is therefore required which will calculate the life remaining in the power module in real time as the device is being used.Because of the high robustness of IGBT power modules, testing for time to failure can be a very lengthy process. A novel procedure and test rig based on Peltier effect thermoelectric coolers was developed, which can automatically temperature cycle IGBT power modules in a very short time and determine their life expectancy, all within their operating specifications. This was tested using several power modules. The failure modes of IGBT power modules are also investigated with a view to developing a failure prediction algorithm. The causes of failure are analysed and a prognostics algorithm is proposed. This prognostics algorithm uses thermal cycle history as a means to predict the life consumed for the power module. The data obtained by the accelerated life tests is used to calculate the coefficients for the prognostic algorithm. A simulation of a vehicle drive cycle is used to show how the prognostics algorithm can be used, and a value indicating the extent to which the IGBT power module has aged is calculated. It is also proved that by intelligently controlling the heat flowing from the heat sink on which the power module is mounted, the life of the IGBT power module can be increased by approximately three times.Hardware and software were developed to implement the health monitoring algorithm. Measurement and control circuits were designed, built and tested together with software that processes the input data, records the thermal cycle history of the IGBT power modules and calculates a value of age for the IGBT power modules in real time. This was tested on several modules to prove the validity of the algorithm.The new algorithms and methodology developed could enable vehicle manufacturers to predict the failure of power modules in hybrid and all electric vehicles. This technology could also benefit other industries such as the renewables (eg wind turbines) and aerospace, where the industry is moving towards all electric aircraft.

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This thesis presents a novel hybrid prognostic methodology, integrating physics-based and data-driven prognostic models, to enhance the prognostic accuracy, robustness, and applicability. The presented prognostic methodology integrates the short-term predictions of a physics-based model with the longer term projection of a similarity-based data-driven model, to obtain remaining useful life estimations. The hybrid prognostic methodology has been applied on specific components of two different engineering systems, one which represents accelerated, and the other a nominal degradation process. Clogged filter and fatigue crack propagation failure cases are selected as case studies. An experimental rig has been developed to investigate the accelerated clogging phenomena whereas the publicly available Virkler fatigue crack propagation dataset is chosen after an extensive literature search and dataset analysis. The filter clogging experimental rig is designed to obtain reproducible filter clogging data under different operational profiles. This data is thought to be a good benchmark dataset for prognostic models. The performance of the presented methodology has been evaluated by comparing remaining useful life estimations obtained from both hybrid and individual prognostic models. This comparison has been based on the most recent prognostic evaluation metrics. The results show that the presented methodology improves accuracy, robustness and applicability. The work contained herein is therefore expected to contribute to scientific knowledge as well as industrial technology development.

Electrical contacts provide a well-proven solution to switching various loads in a wide variety of applications, such as power distribution, control applications, automotive and telecommunications. However, electrical contacts are known for limited reliability due to degradation effects upon the switching contacts due to arcing and fretting. Essentially, the life of the device may be determined by the limited life of the contacts. Failure to trip, spurious tripping and contact welding can, in critical applications such as control systems for avionics and nuclear power application, cause significant costs due to downtime, as well as safety implications. Prognostics provides a way to assess the remaining useful life (RUL) of a component based on its current state of health and its anticipated future usage and operating conditions. In this thesis, the effects of contact wear on a set of electromagnetic relays used in an avionic power controller is examined, and how contact resistance combined with a prognostic approach, can be used to ascertain the RUL of the device. Two methodologies are presented, firstly a Physics based Model (PbM) of the degradation using the predicted material loss due to arc damage. Secondly a computationally efficient technique using posterior degradation data to form a state space model in real time via a Sliding Window Recursive Least Squares (SWRLS) algorithm. Health monitoring using the presented techniques can provide knowledge of impending failure in high reliability applications where the risks associated with loss-of-functionality are too high to endure. The future states of the systems has been estimated based on a Particle and Kalman-filter projection of the models via a Bayesian framework. Performance of the prognostication health management algorithm during the contacts life has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. Prognostic metrics including Prognostic Horizon (PH), alpha-Lamda (α-λ), and Relative Accuracy have been used to assess the performance of the damage proxies and a comparison of the two models made.

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Telemetry Prognostics is Failure Prediction using telemetry for launch vehicle and satellite space flight equipment to stop launch failures, launch pad delays, satellite infant mortalities and satellite on orbit failures. This technology characterizes telemetry behaviors that are latent, transient, and go undetected by the most experienced engineering personnel and software diagnostic tools during integration and test, launch operations and on orbit activities stopping launch pad delays, launch failures, infant mortalities and on orbit failures. Telemetry prognostics yield a technology with state-of-the-art innovative techniques for determining critical on-board equipment remaining useful life taking into account system states, attitude reorientations, equipment usage patterns, failure modes and piece part failure characteristics to increase the reliability, usability, serviceability, availability and safety of our nation’s space systems.

The aim of this study is to propose an alternative approach in prognostics for airborne avionics system in order to enhance maintenance process and aircraft availability. The objectives are to analyse the dependency of avionic systems for fault propagation behaviour degradation, research and develop methods to predict the remaining useful life of avionics Line Replaceable Units (LRU), research and develop methods to evaluate and predict the degradation performances of avionic systems, and lastly to develop software simulation systems to evaluate methods developed. One of the many stakeholders in the aircraft lifecycle includes the Maintenance, Repair and Overhaul (MRO) industry. The predictable logistics process to some degree as an outcome of IVHM gives benefit to the MRO industry. In this thesis, a new integrated numerical methodology called ‘System Level Airborne Avionic Prognostics’ or SLAAP is developed; looking at a top level solution in prognostics. Overall, this research consists of two main elements. One is to thoroughly understand and analyse data that could be utilised. Secondly, is to apply the developed methodology using the enhanced prognostic methodology. Readily available fault tree data is used to analyse the dependencies of each component within the LRUs, and performance were simulated using the linear Markov Model to estimate the time to failure. A hybrid approach prognostics model is then integrated with the prognostics measures that include environmental factors that contribute to the failure of a system, such as temperature. This research attempts to use data that is closest to the data available in the maintenance repair and overhaul industry. Based on a case study on Enhanced Ground Proximity Warning System (EGPWS), the prognostics methodology developed showed a sufficiently close approximation to the Mean Time Before Failure (MTBF) data supplied by the Original Equipment Manufacturer (OEM). This validation gives confidence that the proposed methodology will achieve its objectives and it should be further developed for use in the systems design process.

In the field of cancer research and diagnostics it is crucial to have reliable methods for detecting molecules involved in the disease. New and better methods for diagnostics, prognostics and drug delivery therefore remain a permanent aim. In this thesis applications of the in situ proximity ligation assay (in situ PLA) were developed for diagnostics and research. Two new methods were developed, one more cost effective proximity assay without the use of enzymes and one method for loading pharmaceuticals in lipid rafts made from detergent resistant membranes (DRMs) to be used as a drug delivery platform. In Paper I the aim was to develop a flow cytometric detection method of the fusion protein BCR-ABL that is the hallmark of chronic myeloid leukemia (CML). By using in situ PLA the malignant cells carrying the fusion protein could be detected in patients in a convenient workflow. Paper II describes an application of multiplex in situ PLA, where extracellular vesicles (EVs) are detected and identified using flow cytometry. Up to five different antigens are targeted on the EVs, reflected in three different colors during detection in the flow cytometer. By using antibodies targeting proteins specific for prostasomes a population of prostasomes could be identified in human blood plasma. In Paper III a new method is described for using lipid raft for drug delivery. In this method, lipid rafts, derived from prostasomes or erythrocytes, are loaded with pharmaceuticals. The vehicles were loaded with doxorubicin, added to cells and counted. Cells that received the vehicle with doxorubicin stopped proliferating and died, while controls that received the lipid raft vehicle without doxorubicin were not affected, suggesting that the vehicles are effectively loaded with the drug and that they are safe. This lipid raft vehicle could provide a safe drug delivery system.      Paper IV investigates the crosstalk between the two major signal pathways Hippo and Wnt, and how these are affected in gastric cancer. When looking at different colon cancer tumor stages, we found that the cellular localization of TAZ/β-catenin interactions were different. We also found that protein complexes involved in the crosstalk increased in sparsely growing cells compared to more densely growing cells. On the basis of these results the protein E-cadherin, involved in maintenance of the epithelial integrity, was investigated and was found to have a probable role in regulating the crosstalk between Hippo and Wnt.     A new method for localized protein detection is described in paper V. Here a proximity assay, based on the hybridization chain reaction (HCR), was developed. This assay, proxHCR, is more cost effective than in situ PLA because no enzymes are required. ProxHCR successfully detects protein interactions and can be used together with both fluorescence microscopy and flow cytometry.

DNA microarrays represent an ultra-high throughput gene expression assay employed to study the transcriptomic profiles of biological tissues. These devices are increasingly being used to study many aspects of gene regulation, and there is growing interest in the biotechnology and pharmaceutical industries for developing such devices in efforts toward rational product/drug design. The DNA microarray also provides a unique and objective means for diagnosis and prognosis of human diseases based on patterns of gene expression. This is especially important in cancer research and the thrust toward personalized medicine. This dissertation details the design and development of oligonucleotide microarrays and the design and execution of a gene expression study conducted using human glioma specimines. Chapter 2 details the design and development a ~10,000 gene human oligonucleotide microarray. This device consisted of a 21,168 features, each composed of a particular human gene-probe and was applied to the challenge of diagnostic and prognostic estimation for human gliomas (chapter 3). Gliomas are the most frequent and deadly neoplasms of the human brain characterized by a high misdiagnosis rate and low survival. The study in chapter 3 demonstrated that the specified design and development parameters were appropriate for conducting gene expression analysis and that this platform can be used successfully to predict malignancy grade and survival for glioma patients.

The prime focus of this thesis was to develop a robust Prognostic and Diagnostic Health Management module (PDHM), capable of detecting faults, classifying faults, fault progression tracking and estimating time to failure. Priority was to obtain as much accuracy as possible with the bare minimum amount of sensors as possible. Algorithms like k-Nearest Neighbors (k-NN), Linear and Non- Linear regression and development of rule engine to identify safe operating limits were deployed. The entire solution was developed using R (v 3.5.0). The accuracy of around 98% was obtained in diagnostics. For Prognostics, our ability to predict time to failure more accurately increases with time. Some balance must be there between learning horizon and predicting horizon in order to get good predictions with reasonable time left to hit catastrophic failure. In conclusion, the PDHM module works just as desired and makes Predictive maintenance, smart replacement and crisis prediction possible ensuring the safety and security of people on board and assets.

Rolling element bearing failure can cause problems for industries ranging from mild inconveniences such as simple replacement to catastrophic damage such as large production-line equipment failure. Rolling element bearing failure has plagued industries for many years. Bearings are currently monitored to determine whether or not there is a defect in the bearing, but the remaining lifetime of the bearing remains unknown. This research estimates the bearings remaining lifetime through digital signal processing in conjunction with a modified version of Pariss equationa fatigue-failure equation well known in rotating machinery prognostics. An energy quantity, coined the Power Spectrum Value (PSV), is the maximum amplitude of the frequencies within a relatively small band around the resonant frequency of the system. The current PSV is estimated and updated using a chronologically weighted least squares algorithm. It is this PSV which is implemented in the modified Paris equation to determine the remaining lifetime of the bearing. This research presents a non-intrusive method of determining the lifetime of the bearing so that the bearings utility is maximized and reactive maintenance procedures are minimized.