Chun Lo

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This paper introduces a novel use of concepts from combinatorial group testing and Kalman filtering in detecting faulty sensors in a network when faults are relatively rare. By assigning sensors to specific groups and performing Kalman filter-based fault detection over these groups, we can obtain a small binary detection outcome, which can be decoded to(More)
— Compact and low-cost sensors used in wireless sensor networks are vulnerable to deterioration and failure. As the number and scale of sensor deployments grow, the failure of sensors becomes an increasingly paramount issue. This paper presents a distributed, reference-free fault detection algorithm that is based on local pair-wise verification between(More)
This poster presents a distributed reference-free fault detection algorithm which is based on local pair-wise verification. We show there exist a linear relationship between the output of any pair of sensors if the system excitations can be aggregated as a single system input. Using this relationship, faulty sensors suffering from sparse spike errors can be(More)
Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies non-linear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is(More)
This poster presents a distributed model-based fault detection algorithm which is based on local pair-wise verification. We first show that there exists a linear relationship between the outputs of any pair of sensors. Therefore, a network can be partitioned into sensor pairs, and the relationship between a pair of sensors can be modeled by a linear model.(More)
This poster presents a distributed reference-free fault detection algorithm which is based on local pair-wise verification. We show there exist a linear relationship between the output of any pair of sensors if the system excitations can be aggregated as a single system input. Using this relationship, faulty sensors suffering from sparse spike errors can be(More)
When faulty sensors are rare in a network, diagnosing sensors individually is inefficient. This study introduces a novel use of concepts from group testing and Kalman filtering in detecting these rare faulty sensors with significantly fewer number of tests. By assigning sensors to groups and performing Kalman filter-based fault detection over these groups,(More)
Wireless sensor networks (WSNs) have recently gained the attention of researchers in many challenging aspects. The energy conservation is one of the most important issues in these networks. Due to the limited access to the nodes, both the network structure and the manner of communication between the nodes decide the energy expenditure in WSNs. One of the(More)