Engineering Commons^™

Development Of A Particle Filter-Based Prognostic Model To Predict Maintenance Dependent Processes, Hang Xiao

Doctoral Dissertations

Components and systems in industrial processes undergo wear and degradation until they are either replaced or repaired. Maintenance actions, mostly imperfect repairs, may not entirely reduce the degradation and may expedite future degradation rates. Those repair and maintenance actions should be considered in prognostics models to accurately predict the components’ health conditions.

Different mechanical components have different fault modes in complex engineering systems, such as Nuclear Power Plants (NPPs). The change of a process variable may be caused by the degradation of a few different components. Effective ways to decouple the fault modes are required to predict each component's Remaining …

Integrating Disparate Nuclear Data Sources For Improved Predictive Maintenance Modeling: Maintenance-Based Prognostics For Long-Term Equipment Operation, Zachary Allen Welz

Doctoral Dissertations

The United States (US) nuclear industry is one of the most heavily regulated businesses in the world, creating a culture of world-class design, operation, and maintenance. In an article published on modern maintenance technologies, Terrence OHanlon (past Chief Asset Manager for Reliabilityweb.com) stated, “world class companies often devote up to 50 percent of their entire maintenance resources to condition based monitoring and the planned work that is required as a result of the findings” [1]. One would expect US nuclear power plants to constantly upgrade, improve, and expand their operations and maintenance departments and tactics. Since the early 1990s, US …

Bayesian-Based Methods For Transitioning Between Prognostic Estimates To Leverage Available Data, Alan Y. Nam

Doctoral Dissertations

The availability of failure data directly impacts the empirical prognostic models that can be built. In turn, these models impact the accuracy and uncertainty of remaining useful life (RUL) estimates of systems and components. While ideally a large amount of data of previous failure modes can be collected, the difficulty in obtaining such data can present a significant hurdle. To alleviate the constraints of limited data, Bayesian-based methods of transitioning between different prognostic models were developed. This updating scheme leverages existing data in order to create a unified estimate.

Two novel methods of transitioning are proposed to augment existing prognostic …

Development Of A Method For Incorporating Fault Codes In Prognostic Analysis, Eric Allen Strong

Doctoral Dissertations

Information from fault codes associated with a component may be used as an indicator of its health. A fault code is defined as a timestamp at which a component is not operating according to recommended guidelines. The type of fault codes which are relevant for this analysis represent mild or moderate deviations from normal behavior, rather than those requiring immediate repair. Potentially, fault codes may be used to determine the Remaining Useful Life (RUL) of a component by predicting its failure time, which will improve safety and reduce maintenance costs associated with the component. In this dissertation, methods have been …

Prognostic Approaches Using Transient Monitoring Methods, Michael Eric Sharp

Doctoral Dissertations

The utilization of steady state monitoring techniques has become an established means of providing diagnostic and prognostic information regarding both systems and equipment. However, steady state data is not the only, or in some cases, even the best source of information regarding the health and state of a system. Transient data has largely been overlooked as a source of system information due to the additional complexity in analyzing these types of signals. The development for algorithms and techniques to quickly, and intuitively develop generic quantification of deviations a transient signal towards the goal of prognostic predictions has until now, largely …

Development Of A Prognostic Method For The Production Of Undeclared Enriched Uranium, David Alan Hooper

Doctoral Dissertations

As global demand for nuclear energy and threats to nuclear security increase, the need for verification of the peaceful application of nuclear materials and technology also rises. In accordance with the Nuclear Nonproliferation Treaty, the International Atomic Energy Agency is tasked with verification of the declared enrichment activities of member states. Due to the increased cost of inspection and verification of a globally growing nuclear energy industry, remote process monitoring has been proposed as part of a next-generation, information-driven safeguards program. To further enhance this safeguards approach, it is proposed that process monitoring data may be used to not only …

Merging Data Sources To Predict Remaining Useful Life – An Automated Method To Identify Prognostic Parameters, Jamie Baalis Coble

Doctoral Dissertations

The ultimate goal of most prognostic systems is accurate prediction of the remaining useful life (RUL) of individual systems or components based on their use and performance. This class of prognostic algorithms is termed Degradation-Based, or Type III Prognostics. As equipment degrades, measured parameters of the system tend to change; these sensed measurements, or appropriate transformations thereof, may be used to characterize degradation. Traditionally, individual-based prognostic methods use a measure of degradation to make RUL estimates. Degradation measures may include sensed measurements, such as temperature or vibration level, or inferred measurements, such as model residuals or physics-based model predictions. Often, …