A new wireless sensing network paradigm is presented for structural monitoring applications. In this approach, both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks. Furthermore, the mobile agent provides computational power to make near real-time assessments on the structural conditions. This paper will discuss such prototype systems, which are used to interrogate impedance-based sensors for structural health monitoring applications. Our wireless sensor node is specifically designed to accept various energy sources, including wireless energy transmission, and to be wirelessly triggered on an as-needed basis by the mobile agent or other sensor nodes. The capabilities of this proposed sensing network paradigm are demonstrated in the laboratory and the field.

A variety of intensity-modulated optical displacement sensor architectures have been proposed for use in noncontacting sensing applications, with one of the most widely implemented architectures being the bundled displacement sensor. To the best of the authors' knowledge, the arrangement of measurement fibers in previously reported bundled displacement sensors has not been configured with the use of a validated optical transmission model. Such a model has utility in accurately describing the sensor's performance a priori and thereby guides the arrangement of the fibers within the bundle to meet application-specific performance needs. In this paper, a recently validated transmission model is used for these purposes, and an optimization approach that employs a genetic algorithm efficiently explores the design space of the proposed bundle sensor architecture. From the converged output of the optimization routine, a bundled displacement sensor configuration is designed and experimentally tested, offering linear performance with a sensitivity of -0.066 μm(-1) and displacement measurement error of 223 μm over the axial displacement range of 6-8 mm. It is shown that this optimization approach may be generalized to determine optimized bundle configurations that offer high-sensitivity performance, with an acceptable error level, over a variety of axial displacement ranges. This document has been approved by Los Alamos National Laboratory for unlimited public release (LA-UR 11-03413).

A white light extrinsic Fabry-Perot interferometer is implemented as a noncontacting displacement sensor, providing robust, absolute displacement measurements with micrometer accuracy at a sampling rate of 10 Hz. This paper presents a dynamic model of the sensing cavity between the sensor probe and the nearby target surface using a Fabry-Perot etalon approach obtained from straightforward electromagnetic field formulations. Such a model is important for system characterization, as the dynamically changing cavity length imparts a Doppler shift on any signals circulating within the sensing cavity. Contrary to previously published results, Doppler-induced shifting within the low-finesse sensing cavity is shown to significantly distort the measurement signal as recorded by the sensor. Experimental and simulation results are compared, and the direct effects of cavity dynamics on the measurement signal are analyzed along with their indirect impact on sensor performance. This document has been approved by Los Alamos National Laboratory for unlimited public release (LA-UR 12-00301).

In static tests, low-power (<5 mW) white light extrinsic Fabry-Perot interferometric position sensors offer high-accuracy (μm) absolute measurements of a target's position over large (cm) axial-position ranges, and since position is demodulated directly from phase in the interferogram, these sensors are robust to fluctuations in measured power levels. However, target surface dynamics distort the interferogram via Doppler shifting, introducing a bias in the demodulation process. With typical commercial off-the-shelf hardware, a broadband source centered near 1550 nm, and an otherwise typical setup, the bias may be as large as 50-100 μm for target surface velocities as low as 0.1 mm/s. In this paper, the authors derive a model for this Doppler-induced position bias, relating its magnitude to three swept-filter tuning parameters. Target velocity (magnitude and direction) is calculated using this relationship in conjunction with a phase-diversity approach, and knowledge of the target's velocity is then used to compensate exactly for the position bias. The phase-diversity approach exploits side-by-side measurement signals, transmitted through separate swept filters with distinct tuning parameters, and permits simultaneous measurement of target velocity and target position, thereby mitigating the most fundamental performance limitation that exists on dynamic white light interferometric position sensors.

In this paper, we present experimental investigations using energy harvesting and wireless energy transmission to operate embedded structural health monitoring sensor nodes. The goal of this study is to develop sensing systems that can be permanently embedded within a host structure without the need for an on-board power source. With this approach the required energy will be harvested from the ambient environment, or periodically delivered by a RF energy source to supplement conventional harvesting approaches. This approach combines several transducer types to harvest energy from multiple sources, providing a more robust solution that does not rely on a single energy source. Both piezoelectric and thermoelectric transducers are considered as energy harvesters to extract the ambient energy commonly available on civil structures such as bridges. Methods of increasing the efficiency, energy storage medium, target applications and the integrated use of energy harvesting sources with wireless energy transmission will be discussed.