Transactions of the Institute of Measurement and Control 

About: Transactions of the Institute of Measurement and Control is an academic journal published by SAGE Publishing. The journal publishes majorly in the area(s): Computer science & Nonlinear system. It has an ISSN identifier of 0142-3312. Over the lifetime, 3588 publications have been published receiving 32544 citations.

A particle-filtering approach for on-line fault diagnosis and failure prognosis

Abstract: This paper introduces an on-line particle-filtering (PF)-based framework for fault diagnosis and failure prognosis in non-linear, non-Gaussian systems. This framework considers the implementation of two autonomous modules. A fault detection and identification (FDI) module uses a hybrid state-space model of the plant and a PF algorithm to estimate the state probability density function (pdf) of the system and calculates the probability of a fault condition in realtime. Once the anomalous condition is detected, the available state pdf estimates are used as initial conditions in prognostic routines. The failure prognostic module, on the other hand, predicts the evolution in time of the fault indicator and computes the pdf of the remaining useful life (RUL) of the faulty subsystem, using a non-linear state-space model (with unknown time-varying parameters) and a PF algorithm that updates the current state estimate. The outcome of the prognosis module provides information about the precision and accuracy of long-term predictions, RUL expectations and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary gear plate are used to validate the proposed approach.

Comparison of prognostic algorithms for estimating remaining useful life of batteries

Abstract: The estimation of remaining useful life (RUL) of a faulty component is at the centre of system prognostics and health management. It gives operators a potent tool in decision making by quantifying ...

Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery:

Abstract: Nowadays, the data-driven diagnosis method, exploiting pattern recognition method to diagnose the fault patterns automatically, achieves much success for rotating machinery Some popular classifica

Model-based fault diagnosis in technical processes:

Abstract: In this paper the state-of-the-art developments model-based fault diagnosis in technical processes are reviewed. Attention is focused upon both the analytical approaches that make use of the quantitative models and the knowledge-based approaches using qualitative models. Basic concepts and the advantages as well as disadvantages of different model-based fault diagnosis schemes are outlined.

Physics-of-failure-based prognostics for electronic products:

Abstract: This paper presents a physics-of-failure (PoF)-based prognostics and health management approach for effective reliability prediction. PoF is an approach that utilizes knowledge of a product’s life cycle loading and failure mechanisms to perform reliability design and assessment. PoF-based prognostics permit the assessment of product reliability under its actual application conditions. It integrates sensor data with models that enable in situ assessment of the deviation or degradation of a product from an expected normal operating condition (ie, the product’s ‘health’) and the prediction of the future state of reliability. A formal implementation procedure, which includes failure modes, mechanisms, and effects analysis, data reduction and feature extraction from the life cycle loads, damage accumulation, and assessment of uncertainty, is presented. Then, applications of PoF-based prognostics are discussed.