Tailored piezoelectric thin films for energy harvester

Piezoelectric materials are excellent materials to transfer mechanical energy into electrical energy, which can be stored and used to power other devices. PiezoMEMS is a good way to combine silicon wafer processing and piezoelectric thin film technology and lead to a variety of miniaturized and premium devices. In this thesis, energy harvesters are made, based on epitaxial PZT thin films with enhanced material properties. These vibration energy-harvesting devices consists of a bulk mass attached to a cantilever. In order to increase the performance of energy harvesters, both intrinsic and extrinsic properties in the thin film play a role. For increasing the power output of the devices, we need to seek for piezoelectric thin film with both enhanced piezoelectric coefficient and a lower dielectric constant. Material with a high figure-of-merit (FOM) will be used for energy harvester fabrication. In this work, two ways are used to modify the PZT thin films. First of all, different properties are studied by changing the ratios of Zr and Ti. Secondly, the introduction of additional dopants make the properties of piezoelectric thin film change significantly. After the fundamental study, the epitaxial vibration-harvesting devices are fabricated, which are able to generate energy at microWatt scale with low vibration state. Furthermore, after power normalization, a comparison is made between different vibration harvester. It is concluded that the epitaxial PZT thin film harvester devices outperform the textured PZT and AlN thin film harvesters. To conclude, epitaxial PZT thin film based vibration energy harvesting devices were successfully designed and fabricated. From the material point of view, the crystallographic structure and functional properties of the epitaxial PZT thin films were investigated thoroughly. The physical mechanisms are discussed in each case. Those studies enabled the device specific optimization of the epitaxial PZT thin films. From the application point of view, vibration energy harvester devices with epitaxial piezoelectric thin films were investigated. The strong piezoelectric activity and the outstanding power output in these epitaxial harvesters open the possibility for industrial applications

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

© 2015 American Association of Physicists in Medicine. Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensors) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods

A comparison of modified evolutionary computation algorithms with applications to three-dimensional endoscopic camera motion tracking

© 2017 IEEE. Endoscope 3D motion tracking plays an irreplaceable role for computer-assisted endoscopy systems development. Without such tracking, it is impossible to synchronize pre- and intraoperative images in a reference coordinate frame. Currently available methods are comprised of video-based and electromagnetic tracking. These methods limit to either video image artifacts or inaccurate sensor measurements and dynamic errors. This paper proposes two modified evolutionary computation algorithms: (a) adaptive particle swarm optimization (APSO) and (b) observation-boosted differential evolution (OBDE), to augment current endoscopic camera motion tracking. The experimental results demonstrate that our modified algorithms, which combine endoscopic video images with sensor measurements to estimate endoscope movements, can improve tracking accuracy from 4.8 mm to 2.9 mm. OBDE outperforms APSO for endoscope tracking

Observation-driven adaptive differential evolution and its application to accurate and smooth bronchoscope three-dimensional motion tracking

© 2015 Elsevier B.V. This paper proposes an observation-driven adaptive differential evolution algorithm that fuses bronchoscopic video sequences, electromagnetic sensor measurements, and computed tomography images for accurate and smooth bronchoscope three-dimensional motion tracking. Currently an electromagnetic tracker with a position sensor fixed at the bronchoscope tip is commonly used to estimate bronchoscope movements. The large tracking error from directly using sensor measurements, which may be deteriorated heavily by patient respiratory motion and the magnetic field distortion of the tracker, limits clinical applications. How to effectively use sensor measurements for precise and stable bronchoscope electromagnetic tracking remains challenging. We here exploit an observation-driven adaptive differential evolution framework to address such a challenge and boost the tracking accuracy and smoothness. In our framework, two advantageous points are distinguished from other adaptive differential evolution methods: (1) the current observation including sensor measurements and bronchoscopic video images is used in the mutation equation and the fitness computation, respectively and (2) the mutation factor and the crossover rate are determined adaptively on the basis of the current image observation. The experimental results demonstrate that our framework provides much more accurate and smooth bronchoscope tracking than the state-of-the-art methods. Our approach reduces the tracking error from 3.96 to 2.89. mm, improves the tracking smoothness from 4.08 to 1.62. mm, and increases the visual quality from 0.707 to 0.741