A distributed networked approach for fault detection of large-scale systems

Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available. This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units. The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem. Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique

A Distributed Networked Approach for Fault Detection of Large-scale Systems

Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available. This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units. The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem. Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique

Mobile sink based fault diagnosis scheme for wireless sensor networks

Network diagnosis in Wireless Sensor Networks (WSNs) is a difficult task due to their improvisational nature, invisibility of internal running status, and particularly since the network structure can frequently change due to link failure. To solve this problem, we propose a Mobile Sink (MS) based distributed fault diagnosis algorithm for WSNs. An MS, or mobile fault detector is usually a mobile robot or vehicle equipped with a wireless transceiver that performs the task of a mobile base station while also diagnosing the hardware and software status of deployed network sensors. Our MS mobile fault detector moves through the network area polling each static sensor node to diagnose the hardware and software status of nearby sensor nodes using only single hop communication. Therefore, the fault detection accuracy and functionality of the network is significantly increased. In order to maintain an excellent Quality of Service (QoS), we employ an optimal fault diagnosis tour planning algorithm. In addition to saving energy and time, the tour planning algorithm excludes faulty sensor nodes from the next diagnosis tour. We demonstrate the effectiveness of the proposed algorithms through simulation and real life experimental results

Fault Discrimination in Wireless Sensor Networks

In current times, one of the promising and interesting areas of research is Wireless Sensor Networks. A Wireless Sensor Network consists of spatially distributed sensors to monitor environmental and physical conditions such as temperature, sound, pressure etc. It is built of nodes where each node is connected to one or more sensors. They are used for Medical applications, Security monitoring, Structural monitoring and Traffic monitoring etc. The number of sensor nodes in a Wireless Sensor Network can vary in the range of hundreds to thousands. In this project work we propose a distributed algorithm for detection of faults in a Wireless Sensor Network and to classify the faulty nodes. In our algorithm the sensor nodes are classified as being Fault Free, Transiently Faulty or Intermittently Faulty considering the energy differences from its neighbors in different rounds of the algorithm run. We have shown the simulation results in the form of the output messages from the nodes depicting their health and also compared the results in form of graphs for different average node degrees and different number of rounds of our algorithm run

LEDFD: A Low Energy Consumption Distributed Fault Detection Algorithm for Wireless Sensor Networks

Detection of faulty nodes and network energy saving have become the hottest research topics. Furthermore, current fault detection algorithms always pursue high detection performance but neglect energy consumption. In order to obtain good fault detection performance and save the network power, this paper proposes a low energy consumption distributed fault detection algorithm (LEDFD), which takes full advantage of temporally correlated and spatially correlated characteristics of the sensor nodes. LEDFD utilizes the temporally correlated information to examine some faulty nodes and then utilizes the spatially correlated information to examine the nodes that have not been detected as faulty through exchanging information among neighbor nodes to determine those nodes' state. Because LEDFD takes the data produced by nodes themselves to detect certain types of faults, which means nodes need not exchange information with their neighbor nodes during the entire detection process, the energy consumption of networks is efficiently reduced. Experimental results show that the algorithm has good performance and low energy consumption compared with current algorithms. </jats:p

AN APPROACH FOR FAULT DETECTION AND FAULT MANAGEMENT IN THE WIRELESS SENSOR NETWORK TO EXTEND NETWORK LIFETIME

A mobile wireless ad hoc sensor network (MANET) consists of a group of homogeneous or heterogeneous mobile communicating hosts that form an arbitrary network interconnected via by means of several wireless communication media without any fixed infrastructure. In such network the delivery of the data packet from source to destination may fail for various reasons and major due to failure-prone environment of networks. This may happens due to the topology changes, node failure due to battery exhaust, failure of the communication module in the wireless node and results in the link failure. This paper addressed the major problem of link failure in the WSN and with the aim of providing robust solution so as to satisfy the stern end-to-end requirements of QoS-based communication networks. In this paper we modifies existing fully distributed cluster-based routing algorithm by addressing local recovery for the link failure. Performance of this new fault-tolerant fully distributed cluster-based routing algorithm is evaluated by simulating it in NS2 environment and we show that it performs better than the existing algorithm and provide better solution for fault detection and fault management along the QoS paths

AN APPROACH FOR FAULT DETECTION AND FAULT MANAGEMENT IN THE WIRELESS SENSOR NETWORK TO EXTEND NETWORK LIFETIME

A mobile wireless ad hoc sensor network (MANET) consists of a group of homogeneous or heterogeneous mobile communicating hosts that form an arbitrary network interconnected via by means of several wireless communication media without any fixed infrastructure. In such network the delivery of the data packet from source to destination may fail for various reasons and major due to failure-prone environment of networks. This may happens due to the topology changes, node failure due to battery exhaust, failure of the communication module in the wireless node and results in the link failure. This paper addressed the major problem of link failure in the WSN and with the aim of providing robust solution so as to satisfy the stern end-to-end requirements of QoS-based communication networks. In this paper we modifies existing fully distributed cluster-based routing algorithm by addressing local recovery for the link failure. Performance of this new fault-tolerant fully distributed cluster-based routing algorithm is evaluated by simulating it in NS2 environment and we show that it performs better than the existing algorithm and provide better solution for fault detection and fault management along the QoS paths