Novel vibration residual technology is applied for the first time for detecting a partly-missing (chipped) tooth in a gearbox of the machine fault simulator (MFS). One stage gearbox consists of two bevel gears. The load on the gearbox was applied by a magnetic brake system. An advanced automatic technology for the time synchronous averaging of the raw gear vibrations has been employed; this technology does not require speed data. An advanced technique based on the likelihood ratio is developed for decision making.

Southwest Research Institute (SwRI) investigated the feasibility of integrating remote sensing technology with probability of failure analyses into a monitoring system capable of assessing the structural integrity of critical airframe components. The project demonstrated the viability of remote sensing to discern structural flaw growth along with the integration of sensor data with crack growth analyses in order to assess the health and integrity of a critical structural component.

Composites present additional challenges for inspection due to their heterogeneity and anisotropy, and since damage often occurs beneath their surface. Currently successful laboratory non-destructive methods, such as X-ray and C-scans, are impractical for inspection of large integrated structures. It is clear that new approaches for inspection of composites need to be developed. During the present research, multiple carbon nanotube (CNT) based NDE & SHM techniques were investigated to resolve these issues.

Structural health monitoring provides sensor data that monitor fatigue-induced damage growth in service. This information may in turn be used to improve the characterization of the material properties that govern damage propagation for the structure being monitored. These properties are often widely distributed between nominally identical structures because of differences in manufacturing processes and aging effects. The improved accuracy in damage growth characteristics allows more accurate prediction of the remaining useful life (RUL) of the structural component.

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.

This paper demonstrates the ability to design health monitoring systems from a systematic perspective and, with proper sensor and actuator placement, to detect and track damage occurring in a structure. The results from the first of three separate tests were previously presented showing the daily progression of damage until ultimate failure of the part under test. The tests were performed and the data were collected to emulate on-ground health monitoring scenarios. The data indicate the precursors to total structural failure significantly before the failure occurs.

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.

Fatigue crack initiation and growth during the service of aging aircraft are important life-limiting phenomena. In a previous study, a risk prediction and reliability model for naval aircraft has been developed based on fracture mechanics and inspection field data. Despite significant achievements in the study of fatigue cracks using fracture mechanics, it is still of great interest to find practical techniques for monitoring the crack growth using non-destructive inspection and to integrate the inspection results with the fracture mechanics models to improve the predictions.

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.