Quality-Guaranteed Event-Sensitive Data Collection and Monitoring in Vibration Sensor Networks

• Published in: IEEE transactions on industrial informatics Vol. 13; no. 2; pp. 572 - 583
• Main Authors: Bhuiyan, Md Zakirul Alam, Jie Wu, Guojun Wang, Zhigang Chen, Jianer Chen, Tian Wang
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Computer simulation; Constraints; Data acquisition; Data collection; Data communication; Data reduction; Data transmission; Decision making; Empirical analysis; Energy consumption; Event-sensitive data; Fast Fourier transformations; Informatics; Linearization; Monitoring; Quadrature amplitude modulation; quality of monitoring (QoM); Remote monitoring; resource efficiency; Sensors; Signal processing; Signal processing algorithms; Structural health monitoring; structural health monitoring (SHM); Vibration; vibration data collection; Vibration monitoring; Vibrations; Wireless sensor networks; wireless vibration sensor networks (WVSNs)
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2017.2665463

High-resolution vibration data collection with data quality guaranteeing is important in a class of applications like industrial machine and structural health monitoring. Applying wireless vibration sensor networks (WVSNs) to this class is challenging due to severe resource constraints (e.g., bandwidth and energy). State-of-the-art data reduction approaches (e.g., signal processing, in-network aggregation) suggested to improve these constraints do not satisfy application-specific requirements, e.g., high quality of data (QoD) collection or quality of monitoring (QoM). In this paper, we propose vCollector, a general approach to vibration data collection and monitoring in a resource-constrained WVSN. We enable each sensor to reduce the amount of data (before transmission) in a decentralized manner in two stages: the data acquisition stage and data transmission stage. In the first, we propose a solution to low-complexity signal processing; each sensor analyzes signals using the fast Fourier transform (FFT) under the quadrature amplitude modulation (QAM) and then applies an idea from the Goertzel algorithm (first proposed by Goertzel in 1958) so that the sensor can reduce a significant amount of data without sacrificing the QoD. In the second stage, we propose a decision-making algorithm by which each sensor can make a decision on its acquired data (considered event-sensitive data if it has information about harmful vibrations) so that event-insensitive data communication is reduced. Evaluation results (obtained by simulations using our empirical data traces and by a real system deployment) demonstrate that vCollector significantly reduces energy consumption and guarantees QoM in a WVSN.