IMPACT-BASED PIEZOELECTRIC ENERGY HARVESTING SYSTEM EXCITED FROM DIESEL ENGINE SUSPENSION

Vibration energy harvesting systems are using real ambient sources of vibration excitation. In our paper, we study the dynamical voltage response of the piezoelectric vibrational energy harvesting system (PVEHs) with a mechanical resonator possessing an amplitude limiter. The PVEHs consist of the cantilever beam with a piezoelectric patch. The proposed system was subjected to the inertial excitation from the engine suspension. Impacts of the beam resonator are useful to increase of system’s frequency transition band. The suitable simulations of the resonator and piezoelectric transducer are performed by using measured signal from the engine suspension. Voltage outputs of linear (without amplitude limiter) and nonlinear harvesters were compared indicating better efficiency of the nonlinear design

Digital Signal Processing Research Program

Contains table of contents for Section 2, an introduction, reports on sixteen research projects and a list of publications.Bose CorporationMIT-Woods Hole Oceanographic Institution Joint Graduate Program in Oceanographic EngineeringAdvanced Research Projects Agency/U.S. Navy - Office of Naval Research Grant N00014-93-1-0686Lockheed Sanders, Inc./U.S. Navy - Office of Naval Research Contract N00014-91-C-0125U.S. Air Force - Office of Scientific Research Grant AFOSR-91-0034AT&T Laboratories Doctoral Support ProgramAdvanced Research Projects Agency/U.S. Navy - Office of Naval Research Grant N00014-89-J-1489U.S. Navy - Office of Naval Research Grant N00014-93-1-0686National Science Foundation FellowshipMaryland Procurement Office Contract MDA904-93-C-4180U.S. Navy - Office of Naval Research Grant N00014-91-J-162

Structural Health Monitoring for Composite Materials

Computer networking & communication

Uncertainty Minimization in Robotic 3D Mapping Systems Operating in Dynamic Large-Scale Environments

This dissertation research is motivated by the potential and promise of 3D sensing technologies in safety and security applications. With specific focus on unmanned robotic mapping to aid clean-up of hazardous environments, under-vehicle inspection, automatic runway/pavement inspection and modeling of urban environments, we develop modular, multi-sensor, multi-modality robotic 3D imaging prototypes using localization/navigation hardware, laser range scanners and video cameras. While deploying our multi-modality complementary approach to pose and structure recovery in dynamic real-world operating conditions, we observe several data fusion issues that state-of-the-art methodologies are not able to handle. Different bounds on the noise model of heterogeneous sensors, the dynamism of the operating conditions and the interaction of the sensing mechanisms with the environment introduce situations where sensors can intermittently degenerate to accuracy levels lower than their design specification. This observation necessitates the derivation of methods to integrate multi-sensor data considering sensor conflict, performance degradation and potential failure during operation. Our work in this dissertation contributes the derivation of a fault-diagnosis framework inspired by information complexity theory to the data fusion literature. We implement the framework as opportunistic sensing intelligence that is able to evolve a belief policy on the sensors within the multi-agent 3D mapping systems to survive and counter concerns of failure in challenging operating conditions. The implementation of the information-theoretic framework, in addition to eliminating failed/non-functional sensors and avoiding catastrophic fusion, is able to minimize uncertainty during autonomous operation by adaptively deciding to fuse or choose believable sensors. We demonstrate our framework through experiments in multi-sensor robot state localization in large scale dynamic environments and vision-based 3D inference. Our modular hardware and software design of robotic imaging prototypes along with the opportunistic sensing intelligence provides significant improvements towards autonomous accurate photo-realistic 3D mapping and remote visualization of scenes for the motivating applications