Remaining Useful Lifetime (RUL): Probabilistic Predictive Model

Reliability evaluations and assurances cannot be delayed until the device (system) is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications), by electrical, optical and mechanical measurements and testing; checked (screened) during fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation. Prognostics and health monitoring (PHM) effort can be of significant help, especially at the last, operational stage, of the product use. Accordingly, a simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL) of an electronic device (system) after an appreciable deviation from its normal operation conditions has been detected, and the corresponding increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub curve has been assessed. The general concepts are illustrated by a numerical example. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure) of a device (system) at the operation stage of its lifetime.

A High Fidelity Model Based Approach to Identify Dynamic Friction in Electromechanical Actuator Ballscrews using Motor Current

An enhanced model based approach to monitor friction within Electromechanical Actuator (EMA) ballscrews using motor current is presented. The research was motivated by a drive in the aerospace sector to implement EMAs for safety critical applications to achieve a More Electric Aircraft (MEA). Concerns in reliability and mitigating the single of point of failure (ballscrew jamming) have resulted in consideration of Prognostics and Health Monitoring (PHM) techniques to identify the onset of jamming using motor current. A higher fidelity model based approach is generated for a true representation of ballscrew degradation, whereby the motor is modelled using ‘dq axis’ transformation theory to include a better representation of the motor dynamics. The ballscrew kinematics are to include the contact mechanics of the main sources of friction through the Stribeck model. The simulations demonstrated feature extraction of the dynamic behaviour in the system using Iq current signals. These included peak starting current features during acceleration and transient friction variation. The simulated data were processed to analyse peak Iq currents and classified to represent three health states (Healthy, Degrading and Faulty) using k-Nearest Neighbour (k-NN) algorithm. A classification accuracy of ~74% was achieved.

Prognostics and Health Monitoring Methodologies and Approaches: A Review

Prognostics is a term that engineering borrowed from medicine to refer to the discipline concerned with the Remaining Useful Life (RUL) of an engineering device. This paper surveys the RUL prediction techniques and classifies them into four categories of model-based techniques,knowledge-based techniques, experience-based techniques, and data-driven techniques. A comparative review is given for the main features, prominent advantages, potential shortcomings and main subcategories for each of these categories. The survey is supported by an extensive listfor up-to-date references.

Preliminary analysis on an IVHM approach for prognosis of high-pressure filters for hydraulic Power Control Modules of helicopters

The process of filtration is critical to ensure long operative life to on-board hydraulic equipment, especially in rotating-wing application where the severe vibratory environment lead to accelerated wear of the mechanical components and hence an increased production of debris. Filtration is obtained by mechanically separating the physical contaminants from the hydraulic fluid by means of filters, which hence tend to clog under prolonged usage. Filter replacement has been so far pursued through scheduled maintenance strategy, which however have proven to be rather cost-ineffective. To transition to a Condition-Based Maintenance, new Prognostics and Health Monitoring frameworks need to be developed. The paper deals with the feasibility analysis of such a system based on a high-fidelity simulation environment, rigorous description of the operating conditions and state-of-the-art algorithms.

Prognostics and Health Monitoring of Electro-Hydraulic Systems

Electro-Hydraulic Systems (EHS) are commonly used in many industrial applications. Prediction and timely fault detection of EHS can significantly reduce their maintenance cost, and eliminate the need for redundant actuators. Current practice to detect faults in the actuators can miss failures with combination of multiple sources. Missed faults can result in sudden, unforeseen failures. We propose a fault detection technique based on Multiple Regressor Adaptive Observers (MRAO). The results were evaluated using a two-stage servo-valve model. The proposed MRAO can be used for on-line fault detection. Therefore, we propose a health monitoring approach based on the trend of the identified parameters of the system. Using the history of identified parameters, normal tear and wear of the actuator can be distinguished from the component failures to more accurately estimate the remaining useful life of the actuator.