A Novel Method to Improve the Resolution of Envelope Spectrum for Bearing Fault Diagnosis Based on a Wireless Sensor Node

In this paper, an accurate envelope analysis algorithm is developed for a wireless sensor node. Since envelope signals employed in condition monitoring often have narrow frequency bandwidth, the proposed algorithm down-samples and cascades the analyzed envelope signals to construct a relatively long one. Thus, a relatively higher frequency resolution can be obtained by calculating the spectrum of the cascaded signal. In addition, a 50 % overlapping scheme is applied to avoid the distortions caused by Hilbert transform based envelope calculation. The proposed method is implemented on a wireless sensor node and tested successfully for detecting an outer race fault of a rolling bearing. The results show that the frequency resolution of the envelope spectrum is improved by 8 times while the data transmission remains at a low rate

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Modal analysis and nonlinear characterization of an airborne power ultrasonic transducer with rectangular plate radiator

Some industrial processes like particle agglomeration or food dehydration among others can be enhanced by the use of power ultrasonic technologies. These technologies are based on an airborne power ultrasonic transducer (APUT) constituted by a pre-stressed Langevin-type transducer, a mechanical amplifier and an extensive plate radiator. In order to produce the desired effects in industrial processing, the transducer has to vibrate in an extensional mode driving an extensive radiator in the desired flexural mode with high amplitude displacements. Due to the generation of these high amplitude displacements in the radiator surfaces, non-linear effects like frequency shifts, hysteresis or modal interactions, among others, may be produced in the transducer behavior. When any nonlinear effect appears, when applying power, the stability and efficiency of this ultrasonic technology decreases, and the transducer may be damaged depending on the excitation power level and the nature of the nonlinearity. In this paper, an APUT with flat rectangular radiator is presented, as the active part of an innovative system with stepped reflectors. The nonlinear behavior of the APUT has been characterized numerically and experimentally in case of the modal analysis and experimentally in the case of dynamic analysis. According to the results obtained after the experiments, no modal interactions are expected, nor do other nonlinear effects

Energy managed reporting for wireless sensor networks

In this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio