A technical framework and roadmap of embedded diagnostics/prognostics for complex mechanical systems in PHM systems

Prognostics and Health Management (PHM) technologies have emerged as a key enabler to provide early indications of system faults and perform predictive maintenance actions. While implementing PHM depends on real-time acquiring the present and future health status of a system accurately. For electronic subsystems, built-in-test (BIT) makes it not difficult to achieve these goals. However, reliable prognostics capability is still a bottle-neck problem for mechanical subsystems due to lack of proper on-line sensors. Recent advancements in sensors and micro-electronics technologies have brought about a novel way out for complex mechanical systems, which is called embedded diagnostics/prognostics (ED/EP). ED/EP can provide real-time present condition and prognostic health state by integrating micro-sensors into mechanical structures during design and manufacture, so ED/EP has a revolutionary progress compared to traditional mechanical fault diagnostic/prognostic ways. But how to study ED/EP for complex mechanical systems has not been focused so far. This paper explores the challenges and needs of efforts to implement ED/EP technologies. In particular, this paper presents a technical framework and roadmap of ED/EP for complex mechanical systems. The framework is proposed based on the methodology of system integration and parallel design, which include six key elements (embedded sensors, embedded sensing design, embedded sensors placement, embedded signals transmission, ED/EP algorithms and embedded self-power). Relationships among these key elements are outlined and they should be considered simultaneously during the design of a complex mechanical system. Technical challenges of each key element are emphasized and existed or potential ways to solve each challenge are summarized in detail. Then the development roadmap of ED/EP in complex mechanical systems is brought forward according to potential advancements in related areas, which can be divided into three different stages: individual technology development, system integration and prototype design, and autonomous mechanical systems. In the end, the presented framework is exemplified with a gearbox