Condition assessment and fault prognostics of microelectromechanical systems

Abstract

Microelectromechanical systems (MEMS) are used in different applications such as automotive, biomedical, aerospace and communication technologies. They create new functionalities and contribute to miniaturize the systems and reduce their costs. However, the reliability of MEMS is one of their major concerns. They suffer from different failure mechanisms which impact their performance, reduce their lifetime and their availability. It is then necessary to monitor their behavior and assess their health state to take appropriate decision such as control reconfiguration and maintenance. These tasks can be done by using Prognostic and Health Management (PHM) approaches. This paper addresses a condition assessment and fault prognostic method for MEMS. The paper starts with a short review about MEMS and presents some challenges identified and which need to be raised to implement PHM methods. The purpose is to highlight the intrinsic constraints of MEMS from PHM point of view. The proposed method is based on a global model combining both nominal behavior model and degradation model to assess the health state of MEMS and predict their remaining useful life. The method is applied on a microgripper, with different degradation models, to show its effectiveness.

Optimal Path Evolution in a Dynamic Distributed MEMS-Based Conveyor

“…As in the macro-systems, the degradation of MEMS devices can be modeled by linear or nonlinear functions [14]. In this work, we aim at studying the evolution of the optimal path in a dynamic conveying surface.…”

“…To do so, all MEMS valves involved in conveying the micro-object have to be in a good health state and able to accomplish the mission. However, and according to the literature, the reliability is one of the major concerns of MEMS [14]. They suffer from various failure mechanisms [19,17] which impact their performance, reduce their lifetime, and the availability of systems in which they are utilized.…”

EMA remaining useful life prediction with weighted bagging GPR algorithm

“…RUL prediction also ensures that some measures can be taken in case of the whole aircraft running to failures [22,23,24,25]. Furthermore, RUL prediction allows active replacement, planned maintenance procedures, and enhanced decisions of fleet deploy [15,26]. With wide applications of EMAs, EMA RUL prediction becomes more and more important.…”

Feature extraction for latent fault detection and failure modes classification of board-level package under vibration loadings

“…Vibration can result in deformation of solder joints because of the different flexing between the PCB board and the electronic component during continuous vibration and may lead to the failure of electronics. In capital mission electronics, a failure may result in huge maintenance costs or other unbearable consequences [3]. Therefore, the prognostics and health management (PHM) of electronic package under vibration loadings have been taken attractive by many researchers.…”