A comparative analysis of fault detection schemes for stochastic continuous-time dynamical systems

This paper addresses a comparative analysis of the existing schemes for fault detection in continuous-time stochastic dynamical systems. Such schemes prove to be efficient when dealing with specific types of fault functions; on the other hand, they show very different performance sensitivity when dealing with new fault profiles and system noise. The study suggests the use of a combined scheme, supervised by a high level decision rule set

Outlier detection techniques for wireless sensor networks: A survey

In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree

Reliability Evaluation of Manufacturing Systems: Methods and Applications

The measurement and optimization of the efficiency level of a manufacturing system, and in general of a complex systems, is a very critical challenge, due to technical difficulties and to the significant impact towards the economic performance. Production costs, maintenance costs, spare parts management costs force companies to analyse in a systematic and effective manner the performance of their manufacturing systems in term of availability and reliability (Manzini et al. 2004, 2006, 2008). The reliability analysis of the critical components is the basic way to establish first and to improve after the efficiency of complex systems. A number of methods (i.e. Direct Method, Rank Method, Product Limit Estimator, Maximum likelihood Estimation, and others (Manzini et. Al., 2009) all with reference to RAMS (Reliability, Availability, Maintainability and Safety) analysis, have been developed, and can bring a significant contribution to the performance improvement of both industrial and non-industrial complex systems. Literature includes a huge number of interesting methods, linked for example to preventive maintenance models; these models can determine the best frequency of maintenance actions, or the optimization of spare parts consumption or the best management of their operating costs (Regattieri et al., 2005, Manzini et al., 2009). Several studies (Ascher et al..1984, Battini et al., 2009, Louit et al., 2007, Persona et al. 2007) state that often these complex methodologies are applied using false assumptions such as constant failure rates, statistical independence among components, renewal processes and others. This common approach results in poor evaluations of the real reliability performance of components. All subsequent analysis may be compromised by an incorrect initial assessment relating to the failure process. A correct definition of the model describing the failure mode is a very critical issue and requires efforts which are often not sufficiently focused on. In this chapter the author discusses the model selection failure process, from the fundamental initial data collection phase to the consistent methodologies used to estimate the reliability of components, also considering censored data. This chapter introduces the basic analytical models and the statistical methods used to analyze the reliability of systems that constitute the basis for evaluation and prediction of the stochastic failure and repair behavior of complex manufacturing systems, assembled using a variety of components. Consequently, the first part of the chapter presents a general framework for components which describes the procedure for the solution of the complete Failure Process Modeling (FPM) problem, from data collection to final failure modeling, that, in particular, develops the fitting analysis in the renewal process and the contribution of censored data throughout the whole process. The chapter discusses the main methods provided in the proposed framework. Applications, strictly derived from industrial case studies, are presented to show the capability and the usefulness of the framework and methods proposed

Outlier Detection Techniques For Wireless Sensor Networks: A Survey

In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the multivariate nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a decision tree to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier degree

Fault isolation schemes for a class of continuous-time stochastic dynamical systems

In this paper a new method for fault isolation in a class of continuous-time stochastic dynamical systems is proposed. The method is framed in the context of model-based analytical redundancy, consisting in the generation of a residual signal by means of a diagnostic observer, for its posterior analysis. Once a fault has been detected, and assuming some basic a priori knowledge about the set of possible failures in the plant, the isolation task is then formulated as a type of on-line statistical classification problem. The proposed isolation scheme employs in parallel different hypotheses tests on a statistic of the residual signal, one test for each possible fault. This isolation method is characterized by deriving for the unidimensional case, a sufficient isolability condition as well as an upperbound of the probability of missed isolation. Simulation examples illustrate the applicability of the proposed scheme

A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation

Aircraft engine manufacturers collect large amount of engine related data during flights. These data are used to detect anomalies in the engines in order to help companies optimize their maintenance costs. This article introduces and studies a generic methodology that allows one to build automatic early signs of anomaly detection in a way that is understandable by human operators who make the final maintenance decision. The main idea of the method is to generate a very large number of binary indicators based on parametric anomaly scores designed by experts, complemented by simple aggregations of those scores. The best indicators are selected via a classical forward scheme, leading to a much reduced number of indicators that are tuned to a data set. We illustrate the interest of the method on simulated data which contain realistic early signs of anomalies.Comment: Proceedings of the 14th Industrial Conference, ICDM 2014, St. Petersburg : Russian Federation (2014

Detection and Isolation of Simultaneous Additive and Parametric Faults in Nonlinear Stochastic Dynamical Systems

This paper presents a new fault detection and isolation scheme for dealing with simultaneous additive and parametric faults. The new design integrates a system for additive fault detection based on Castillo and Zufiria, 2009 and a new parametric fault detection and isolation scheme inspired in Munz and Zufiria, 2008 . It is shown that the so far existing schemes do not behave correctly when both additive and parametric faults occur simultaneously; to solve the problem a new integrated scheme is proposed. Computer simulation results are presented to confirm the theoretical studies