development of monitoring systems to fault detection, in offensive and defensive systems, uav, aircraft and other complex systems technically make it possible and favorable, predictive diagnosis of faults. health management model and predict equipment failures (phm) were created in recent years by formation a strong bond of science in engineering, computer and reliability. for this reason, more...

This paper presents efficient methods for online fault detection and diagnosis of Network-on-Chip (NoC) switches. The fault model considered in this research is a system level fault model based on the generic properties of NoC switch functionality. The proposed method is evaluated by fault simulation in a platform using this system level fault model. The experimental results show that with a re...

This paper investigates the problem of fault detection and diagnosis (FDD) problem for non-Gaussian singular stochastic distribution control (SDC) systems via the output probability density functions(PDFs). The PDFs can be approximated by using square-root B-spline expansion, via this expansions to represent the dynamics weighting systems between the system input and the weights related to the ...

Chemical processes are systems that include complicated network of material, energy and process flow. As time passes, the performance of chemical process gradually degrades due to the deterioration of process equipments and components. The early detection and diagnosis of faults in chemical processes is very important both from the viewpoint of plant safety as well as reduced manufacturing cost...

In this paper, a new fast and accurate method for fault detection, location, and classification on multi-terminal DC (MTDC) distribution networks connected to renewable energy and energy storages presented. MTDC networks develop due to some issues such as DC resources and loads expanding, and try to the power quality increasing. It is important to recognize the fault type and location in order ...

This paper deals with the fault severity detection and diagnosisof induction motor fault based on image processing using particle analysis. Index of compactness and distance between xc coordinate of gravity center of the region and x coordinate of the mean upper point of the region (dist_xc_tlr) are two features extracting by image processing. Using the fuzzy logic strategy, a better understand...

Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient approach for detecting outliers in sensed data in a WSN. The outliers in sensed data can be ca...

A state-based approach for on-line passive fault diagnosis in systems modelled as finite-state automata is presented. In this framework, the system and the diagnoser (the fault detection system) do not have to be initialized at the same time. Fhrthermore, no information about the state or even the condition (failure status) of the system before the initiation of diagnosis is required. The desig...