Piezoelectric Structural Excitation using a Wireless Active Sensing Unit

Strong interest in applying wireless sensing technologies within structural monitoring systems has grown in recent years. Wireless sensors are capable of passively collecting response measurements of a dynamic structural system at low-costs. However, the role of wireless sensing within structural monitoring systems can be expanded if sensors are provided a direct interface to the physical system in which they are installed. Capable of exciting a structural system through actuators, a wireless “active” sensor would be a valuable tool in structural control and damage detection applications. In this study, a wireless active sensing unit is proposed and fabricated. After fabrication of a prototype, a series of validation tests are conducted to assess the unit’s performance. A piezoelectric pad mounted to an aluminum plate is commanded by the wireless active sensing unit to impart lowenergy Lamb waves in the plate surface. Simultaneously, the same unit collects response measurements obtained from a second piezoelectric pad also surface mounted to the plate. To illustrate the potential of the wireless active sensing unit to locally perform system identification analyses, the computational core is provided the task of calculating autoregressive time-series models using input-output time-history data collected from the excited system. INTRODUCTION Civil structures including bridges, buildings and pipelines, are expensive assets often exposed to harsh loading environments. Over their operational life spans, the loading regime of structures can be so severe that wear and tear deterioration is common. Furthermore, structures located in zones of high seismic activity are vulnerable to extreme loadings resulting from earthquakes. Even though design codes ensure the global collapse of structures is avoided during earthquakes, significant structural damage can still occur. For example, during the 1994 Northridge earthquake, over $20 billion worth of structural damage was sustained within the greater Los Angeles metropolitan region [1]. In light of these facts, facility owners (both government and private) have expressed a strong desire to instrument their structural inventories with monitoring systems. Response measurements collected during ambient and forced excitations can be analyzed for better understanding of the behavior of structural designs as well as to potentially identify occurrences of structural damage. Currently, monitoring systems designed explicitly for civil structures make extensive use of coaxial cables to transfer measurements from embedded sensors (often accelerometers and strain gages) to centralized data servers. The centralized architectural configuration is a result of structural monitoring systems having originated from centralized data acquisition systems used within laboratory settings. While structural monitoring systems have proven to be a reliable and accurate technology, their installations are expensive. For example, recent system installations conducted by the United States Geological Survey (USGS) have cost over $5,000 per channel with 12-channel systems costing well over $60,000 [2]. A large fraction of the cost can be attributed to the installation of the coaxial cables. For structures situated in harsh weather environments, such as long-span bridges over water, installation costs can increase because cables must be installed within weather-proof conduits. Academic and industrial researchers are currently exploring the adoption of information technologies, such as wireless communications and embedded computing, within structural monitoring systems. Adoption of these technologies has the potential to provide future monitoring systems with enhanced functionality at substantially reduced costs. To address the high installation costs of current tethered systems, the early work of Straser and Kiremidjian illustrated wireless communications could be a cost-effective and reliable substitute for coaxial cables [3]. Lynch et al. has extended their work with the design of a wireless structural monitoring system assembled from a network of intelligent wireless sensing units capable of autonomous operation [4]. A key innovation proposed by Lynch et al. is a sophisticated computational core that can execute on-board engineering algorithms using measurement data stored in memory; embedded microcontrollers are used as the major hardware component of the computational core design. To illustrate the utility of such a core design, a statistical patternrecognition approach to damage detection was embedded and locally executed to successfully identify damage within a laboratory test structure [5]. With computational power tightly coupled with each sensing transducer, a decentralized computational framework arises. Some advantages associated with computational decentralization include parallel processing of measurement data, elimination of single point-of-failure vulnerabilities and opportunities for large-scale installations. A wireless structural monitoring system with on-board computational power is well suited to potentially be used as a structural health monitoring system. Structural health monitoring systems autonomously collect structural response data and process the data to identify the occurrence and location of structural damage. In order for future structural health monitoring systems to be attractive for industry adoption, damage detection algorithms embedded must be accurate and reliable. A large number of researchers have illustrated the successes and failures of different damage detection algorithms when applied to a broad class of structural systems [6]. Due to normal environmental and operational variability, many of the proposed damage detection methods have been difficult to apply to civil structures. For example, damage detection methods that consider changes in global modal properties are hindered by modal properties also exhibiting sensitivity to temperature [7]. In response to these limitations, a multi-tiered time-series approach that uses pattern classification techniques to identify structural damage has been proposed. The time-series approach has been successfully applied to various laboratory and field structures including the hull of a fast patrol boat performing within a changing operational environment [8]. The focus of this study is to extend the capabilities of a wireless sensing unit design to include an interface to which actuators can be attached. Termed a wireless active sensing unit, the monitoring system can now command actuators to excite or control a structural system. No longer solely passive elements responsible for data collection, the proposed wireless active sensing unit can have an active influence on the structural system at both a global and local level. For example, wireless active sensing units can be used for global structural control with units collecting data from sensors, calculating actuation forces and then commanding semi-active variable dampers. In this study, the actuation interface will serve as a mechanism for exciting individual structural elements with low-energy surface waves. Using piezoelectric pads mounted to the surface of structural elements, Lamb waves can be simultaneously transmitted and received by a single wireless active sensing unit. In contrast to global damage-detection procedures, the controllable low-energy excitation provided by piezoelectric pads can be used to perform damage detection at the local element level. For example, changes in Lamb wave properties correlated to damage can be detected using processing algorithms embedded in the unit core. An additional advantage associated with locally actuated excitations is that they are completely repeatable unlike ambient and seismic excitations. In this paper, the design of a wireless active sensing unit for potential use in a structural health monitoring system is presented. To validate the performance of the proposed design, an aluminum plate with two piezoelectric elements epoxy mounted to its surface will be used. The wireless unit will command one piezoelectric pad to emit white noise surface waves while the sensing interface simultaneously records attenuated waves as received at the second pad. To illustrate the use of the computational core’s ability to interrogate response data, the wireless sensing unit will locally execute numerical algorithms that calculate the transfer function and autoregressive exogenous input (ARX) time-series model of the structural element. DESIGN OF A WIRELESS ACTIVE SENSING UNIT The wireless active sensing unit is intended to 1) collect measurement data from sensors embedded within structural elements that are excited by low-energy actuation elements, 2) store, manage and locally process the measurement data collected, and 3) to communicate data and results to a wireless sensing network comprised of other wireless sensing/actuation agents. To accomplish the specified operational tasks, the design of the wireless active sensing unit is divided into four functional subsystems as shown in Figure 1: the sensor interface, actuation interface, computational core, and wireless communication channel. The design procedure of each of the four subsystems will emphasize use of off-the-shelf components that satisfy the unique performance requirements of the unit. The sensing and actuation interfaces will be designed as actuatorand sensor-transparent, meaning any analog sensor or actuator, including piezoelectric elements, can be easily integrated with the system. However, the high-frequency operational regimes of piezoelectric elements will require data acquisition and control interfaces with quick real-time responses, well above 1 kHz. The performance goals of the sensing and actuation interfaces represent a significant challenge of the proposed unit design; as such, other design issues such as power consumption characteristics will not be considered in this study. At the center of the wireless active sensing unit design is the computational core. Similar to previously proposed wireless sensing unit designs, the 32-bit Motorola MPC555 PowerPC microcontroller is selected as the core’s primary hardware component. Selection of the MPC555 was motivated by its high-speed clock frequency (40 MHz) and its sophisticated internal arithmetic and logic unit with on-chip floating point calculations. High processor speeds are necessary to operate the high-frequency piezoelectric elements to be connected to the unit sensing and actuation interfaces. Internally integrated with this fast processor is 448 Kbytes of read only memory (ROM) where firmware will be stored for unit operation and embedded data processing. Since only 26 Kbytes of internal random access memory (RAM) is included in the MPC555, 512 Kbytes of external static RAM (SRAM) is added to the unit design for data storage. The read and write operations to the external memory take two clock cycles to complete and are slower than those to internal memory that take one cycle. Therefore, for applications demanding high-sample rates, data collected from the sensing interface will be written first to internal memory. After the data has been collected and real-time constraints no longer in effect, the measurement data will be transferred automatically from internal to external memory. Figure 1 – Architectural design of the proposed wireless active sensing unit Wireless Modem 900 MHz ISM Band Spread Spectrum Encoding Proxim ProxLink Wireless Modem Computational Core Sensing Interface Multi-Channel Analog-Digital Converter (ADC) 10-bit Resolution MPC555 -5V