An experimental investigation of the data delivery performance of a wireless sensing unit designed for structural health monitoring

This study explores the reliability of a wireless sensing unit by testing it in a real-world university laboratory environment. The unit employs off-the-shelf products for their key components, while a flexible payload scheme was adopted for radio packet transmission to maximize throughput and minimize latency. The testing consists of two main parts: (1) a series of loopback tests using two off-the-shelf radio components with carrier frequencies of 900 MHz and 2.4 GHz, respectively, and (2) wireless transmission of a shake table response to a periodic swept sine excitation. The performance of the wireless channel is examined in each part of the study. Through this experimental investigation, it is validated that a loopback test may be used as a fast prototyping approach to characterize the complex transmitting environment of a structure in which a wireless monitoring system is installed. Various factors leading to signal attenuation are ranked according to their effects on packet delivery performance. Transmitting range and building materials are among the leading factors causing packet loss (and therefore data loss) in this specific testing environment. The severity of interference from 802.11b wireless systems in close proximity to the wireless sensing unit was investigated. Some preliminary results on the influence of operating rotating machinery and human activities are to wireless sensors were investigated. The results presented herein offer a guideline for applying wireless sensing within real-world structures so that the reliability of the wireless monitoring system is maximized. Due to uncertainties associated with the reliability of wireless communications, statistical analysis is performed on the collected time histories to reveal the underlying patterns associated with data loss. Temporal correlations of data loss were measured and found to be related to the adopted radio. A statistical distribution of the size of consecutive lost data points was further derived from the collected data. Such results have identified the need to further develop: (1) reliable communication protocols to reduce these losses in data and information, and (2) robust data processing and system identification tools to anticipate and explicitly handle any data loss. Copyright © 2007 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60229/1/205_ftp.pd