A multiscale principal component analysis method is proposed for sensor fault detection and identification. After decomposition of sensor signal by wavelet transform, the coarse-scale coefficients from the sensors with strong correlation are employed to establish the principal component analysis model. A moving window is designed to monitor data from each sensor using the model. For the purpose...

In engineering application the sensor or actuator fault will lead to seriously damage to mechanical systems. The research of sensor or actuator fault diagnosis and fault-tolerant control is very important to improve the safety and reliability of the system. The paper investigates the fault diagnosis and fault-tolerant methods of vehicle suspension system with Magnetorheological (MR) dampers (ac...

Most indoor localization systems are based on static sensor nodes with known position. By means of this infrastructure and measured distances to the static nodes, mobile nodes can localize themselves. But a major problem is the manual position determination of all static sensor nodes, since this procedure is time consuming and fault-prone. In this paper, we present Distribute & Erase, a self-ca...

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventiona...

In wireless sensor networks, the limited battery resources of sensor nodes have a direct impact on network lifetime. To improve energy efficiency, there have been a variety of sensor node scheduling methods to keep only a minimum number of sensor nodes in active mode. However, those existing sensor node scheduling methods mainly focus on the coverage problems, largely ignoring the fault-toleran...

Modeling faults and malicious activities in sensor networks can be challenging. Designing and re-evaluating a “good” classifier to detect abnormalities imposes yet another challenge once the sensor network is deployed in the field. Common approaches among researchers involve obtaining publicly accessible labeled datasets, generating synthetic sensor data, or collecting sensor readings from a re...

This article describes the implementation of early warning feature in an over-current protection module designed for limiting the surgecurrent in communication applications. The early warning signal is generated by a surge-current sensor and a temperature sensor mounted on the protection module. Described solution decreases fault latency and consequently improves the efficiency of the on-line f...

Wireless sensor networks (WSN) are composed of a large number of sensor nodes and usually used to monitor a region of interest. The sensor nodes are very prone to damage due to low-cost design and random deployment. Additionally, faulty nodes may degrade the performance of the distributed hypothesis testing. This work addresses fault isolation in WSN where the fusion center attempts to identify...