Advances in additive manufacturing techniques have enabled the creation of stimuli-responsive materials with designed three-dimensional (3D) architectures. Unlike biological systems in which functions such as sensing, actuation, and control are closely integrated, few architected materials have comparable system complexity. We report a design and manufacturing route to create a class of robotic metamaterials capable of motion with multiple degrees of freedom, amplification of strain in a prescribed direction in response to an electric field (and vice versa), and thus, programmed motions with self-sensing and feedback control. These robotic metamaterials consist of networks of piezoelectric, conductive, and structural elements interwoven into a designed 3D lattice. The resulting architected materials function as proprioceptive microrobots that actively sense and move.

For the past five years, cantilevered beams with piezoceramic layer(s) have been frequently used as piezoelectric energy harvesters for vibration-to-electric energy conversion. Typically, the energy harvester beam is located on a vibrating host structure and the dynamic strain induced in the piezoceramic layer(s) results in an alternating voltage output across the electrodes. Vibration modes of a cantilevered piezoelectric energy harvester other than the fundamental mode have certain strain nodes where the dynamic strain distribution changes sign in the direction of beam length. It is theoretically explained and experimentally demonstrated in this paper that covering the strain nodes of vibration modes with continuous electrodes results in strong cancellations of the electrical outputs. A detailed dimensionless analysis is given for predicting the locations of the strain nodes of a cantilevered beam in the absence and presence of a tip mass. Since the cancellation issue is not peculiar to clamped-free boundary conditions, dimensionless data of modal strain nodes are tabulated for some other practical boundary condition pairs and these data can be useful in modal actuation problems as well. How to avoid the cancellation problem in energy harvesting by using segmented electrode pairs is described for single-mode and multimode vibrations of a cantilevered piezoelectric energy harvester. An electrode configuration-based side effect of using a large tip mass on the electrical response at higher vibration modes is discussed theoretically and demonstrated experimentally.

As the maliciousness and frequency of cyber-attacks continues to grow, the safety and security of cyber-physical critical infrastructures, such as manufacturing, is quickly becoming a significant concern across the globe. Outside of traditional intellectual property theft, attacks against manufacturing systems pose a threat to maintaining a product's design intent. More specifically, such attacks can alter a manufacturing system to produce a part incorrectly; resulting in impaired functionalities or reduced performance. Manufacturing systems rely heavily upon the use of quality control systems to detect quality losses and to ensure the continued production of high-quality parts. However, quality control systems are not designed to detect the effects of malicious attacks and are ill-suited to act as a cyber-security measure for many manufacturing systems. Therefore, this paper presents a novel product/process design approach to enable real-time attack detections to supplement the shortcomings of quality control systems. The proposed approach, inspired by side-channel schemes used to detect Trojans (foreign malicious logic) in integrated circuits, aims at detecting changes to a manufactured part's intrinsic behavior through the use of structural health monitoring techniques

The ability to classify the gender of occupants in a building has far-reaching applications including security and retail sales. The authors demonstrate the success of machine learning techniques for gender classification. High-sensitivity accelerometers mounted noninvasively beneath an actual building floor provide the input for these machine learning methods. While other approaches using gait measurements, such as vision systems and wearable sensors, provide the potential for gender classification, they each face limitations. These limitations include an invasion of privacy, occupant compliance, required line of sight, and/or high sensor density. Underfloor mounted accelerometers overcome these limitations. The authors utilize the highly-instrumented Goodwin Hall smart building on the Virginia Tech campus to measure vibrations of the walking surface caused by walkers. In this paper, the gait of 15 individual walkers was recorded as they, alone, walked down the instrumented hallway. Fourteen accelerometers, mounted underneath the walking surface, recorded walking trials with the placement of the sensors unknown to the walker. This paper studies bagged decision trees, boosted decision trees, support vector machines, and neural networks as the machine learning techniques for their ability to classify gender. A tenfold-cross-validation method is used to comment on the validity of the algorithm's ability to generalize to new walkers. This paper demonstrates that a gender classification accuracy of 88% is achievable using the underfloor vibration data from the Virginia Tech Goodwin Hall by using decision tree approaches.

Mechanical waves are induced in solids due to the system’s coupling with an external excitation. Depending upon the nature of the resulting displacement and phase difference between the vibrating particles at a particular frequency, the mechanical waves can be classified as standing waves, traveling waves or a combination of the two. This study focuses on the identification of these different forms of mechanical waves and discusses methods that can be suitably used for their classification. The Hilbert and Fourier methods of classification were validated using experimental results and then compared against each other. The experimental and theoretical analysis of mechanical waves was conducted on a beam with free-free boundary conditions excited by piezoelectric elements.