This paper presents a methodology to quantify the uncertainty in fatigue damage prognosis, applied to structures with complicated geometry and subjected to variable amplitude multi-axial loading. The crack growth analysis uses the concept of equivalent initial flaw size to replace small crack growth calculations and make use of a long crack growth model. A Gaussian process surrogate model, trained by a few finite element runs, is used to calculate the stress intensity factor used in crack growth calculation, as a function of crack size and loading.

In this paper we present a statistical approach to the estimation of the time in which an operating gear will achieve the critical stage. The approach relies on measured vibration signals. From these signals features are extracted first and then their evolution over time is predicted. This is accomplished using a dynamic model that relates hidden degradation phenomena with measured outputs. The Expectation-Maximization algorithm is used to estimate the parameters of the underlying state-space model on-line.

Aircraft engine bearing prognosis not only requires early detection of a bearing defect, but also the ability to predict bearing health conditions given certain operational scenarios. This paper summarizes a physics-based remaining useful life prediction method developed in the DARPA engine system prognosis (ESP) program. This investigation focuses on a typical roller bearing fault (or defect) on the outer raceway. Spall detection is based on the fusion of vibration and online oil debris sensors.

Rolling element bearings are key components in most rotating machinery. It is necessary to determine the condition of the bearing with reasonable degree of confidence. Many techniques have been developed for bearing fault detection. Each of these techniques have their own strengths and weaknesses. In this paper various features are compared for detecting inner race defects in rolling element bearings. Mutual information between the feature and defect is used as a quantitative measure of quality and the features are ranked appropriately.

Actuator systems are employed widely in aerospace, transportation and industrial processes to provide power to critical loads, such as aircraft control surfaces. They must operate reliably and accurately in order for the vehicle / process to complete successfully its designated mission. Incipient actuator failure conditions may severely endanger the operational integrity of the vehicle / process and compromise its mission.

In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an underlying physics-based crack growth model. Various uncertainties from measurements, modeling, and parameter estimations are considered to describe the stochastic process of fatigue damage accumulation. A probabilistic prognosis updating procedure based on the maximum relative entropy concept is proposed to incorporate measurement data.