Ocean waves can provide a renewable and secure energy supply to coastal residents around the world. Yet, to safely harness and convert the available energy, issues such as bearing reliability and maintainability need to be resolved. This paper presents the application of a PHM based research methodology to derive empirical models for estimating the wear of polymer bearings installed on wave energy converters. Forming the foundation of the approach is an applicable wave model, sample data set, and experimental test stand to impose loading conditions similar to that expected in real seas.

There are many facets of a prognostics and health management system.

Two key impediments for the commercial success of model-based diagnosis (MBD) include (a) a lack of component libraries for more cheaply and efficiently building MBD models, and (b) a failure to integrate the development of embedded MBD code within the design process. This article addresses both of these impediments by providing a formal framework that integrates component-based design with MBD modeling. The proposed framework extends the consistency-based theory of MBD with a component-based design theory based on contracts. The contributions of the article are as follows:

Unmanned Air Systems (UAS) show great promise for a range of civilian applications, especially ‘dull, dirty or dangerous’ missions such as air-sea rescue, coastal and border surveillance, fisheries protection and disaster relief. As the demand for autonomy increases, the importance of correctly identifying and responding to faults becomes more apparent, as fully autonomous systems must base their decisions solely upon the sensors readings they receive – as there is no human on board.

Prognostics performance evaluation has gained significant attention in the past few years. As prognostics technology matures and more sophisticated methods for prognostic uncertainty management are developed, a standardized methodology for performance evaluation becomes extremely important to guide improvement efforts in a constructive manner. This paper is in continuation of previous efforts where several new evaluation metrics tailored for prognostics were introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics.

FMEA(Failure Mode and Effects Analysis) is a systematic method of identifying and preventing system, product and process problems. As a standard document, FMEA is produced during the design of products or systems. However, FMEA documentation is rarely validated or updated in practice after it was generated. FMEA validation remains a challenge. In this technical report, we propose to validate FMEA using historical operation and maintenance data. First, we need to verify linkages between FMEA and corresponding operational and maintenance data.

Differential protection is a popular method to protect aircraft generators against winding faults. Traditional relay-based systems have a limited capability to distinguish between differential current resulting from a winding fault, and the one resulting from measurement noise or current saturation, resulting in false alarms and unnecessary equipment shutdown. Modern aircraft generators are monitored and controlled by advanced generator control units, and therefore, sophisticated signal processing algorithms can be implemented to enhance the differential protection performance.

Modern complex systems have evolved into artifacts that rely on both hardware and software to dependably function without human control. Health management software control systems have been developed to manage failures in such complex systems. The Prognostics and Health Management (PHM) systems have also developed to detect and identify failures and support operation by guiding either operator or automated software response.

The U.S. Army Program Management Office, Heavy Brigade Combat Team (PM-HBCT) is working towards embedding enhanced diagnostic and prognostic capabilities onto the current fleet of HBCT ground vehicles – including the M1A2 SEPv2, M1A1 AIM, M2A2 ODS/SA, M2A3, M109A6 Paladin PIM, and the M88A2 – through the Vehicle Health Management System (VHMS).

A prognostics and health management (PHM) system is the focus of attention in the Defense Acquisition University’s LOG 201 Intermediate Acquisition Logistics course. LOG 201 is a one-week case-based course required for Level II certification in the Department of Defense Life-cycle Logistics career field, as required by the Defense Acquisition Workforce Improvement Act (DAWIA). In this hypothetical case, the PHM System is to be embedded in the Strike Talon Unmanned Combat Aircraft System for use by the United States Air Force and Navy.