Tracking and erosion resistance of silicone rubber nanocomposites under positive and negative dc voltages

ASTM D2303 standard provides a method for evaluating the tracking and erosion resistance of polymeric insulators under ac voltages. In this paper, the above method has been extended for evaluating the performance of the insulators under dc stresses. Tests were conducted on polymeric silicone rubber (SR) insulators under positive and negative dc stresses. Micron sized Alumina trihydrate (uATH) and nano sized Alumina (nALU) were used as fillers in SR matrix to improve the resistance to tracking and erosion. Results suggest that SR composites perform better under negative dc than under positive dc voltages. Eroded mass and leakage current data support the above result. Samples with low concentration of nano alumina fillers performed on par with the samples with large loadings of uATH.

Tracking and Erosion of Silicone Rubber Nanocomposites under DC Voltages of both Polarities

In order to improve the tracking and erosion performance of outdoor polymeric silicone rubber (SR) insulators used in HV power transmission lines, micron sized inorganic fillers are usually added to the base SR matrix. In addition, insulators used in high voltage dc transmission lines are designed to have increased creepage distance to mitigate the tracking and erosion problems. ASTM D2303 standard gives a procedure for finding the tracking and erosion resistance of outdoor polymeric insulator weathershed material samples under laboratory conditions for ac voltages. In this paper, inclined plane (IP) tracking and erosion tests similar to ASTM D2303 were conducted under both positive and negative dc voltages for silicone rubber samples filled with micron and nano sized particles to understand the phenomena occurring during such tests. Micron sized Alumina Trihydrate (ATH) and nano sized alumina fillers were added to silicone rubber matrix to improve the resistance to tracking and erosion. The leakage current during the tests and the eroded mass at the end of the tests were monitored. Scanning Electron Microscopy (SEM) and Energy dispersive Xray (EDX) studies were conducted to understand the filler dispersion and the changes in surface morphology in both nanocomposite and microcomposite samples. The results suggest that nanocomposites performed better than microcomposites even for a small filler loading (4%) for both positive and negative dc stresses. It was also seen that the tracking and erosion performance of silicone rubber is better under negative dc as compared to positive dc voltage. EDX studies showed migration of different ions onto the surface of the sample during the IP test under positive dc which has led to an inferior performance as compared to the performance under negative dc.

A mixture model approach for formant tracking and the robustness of student's-t distribution

We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

An Optoelectronic Profiling and Ranging Sensor for Monitoring of Perimeters

Electronic monitoring of perimeters plays vital roles in homeland security, management of traffic and of humanwildlife conflict. This paper reports the design and development of an optical beam-interruption-based ranging and profiling sensor for monitoring perimeters. The developed sensor system can determine the distance of the object from the sensing units and its temporal height profile as the object crosses the system. Together, these quantities can also be used to classify the object and to determine its speed. The sensor is designed, fabricated, and evaluated. The design enables compact construction, high sensitivity, and low measurement crosstalk. The evaluation demonstrates accuracy better than 98.5% in the determination of height and over 94% in determination of the distance of an object from the sensing units. Finally, a strategy is proposed to classify the objects based on the obtained height profiles. The strategy is demonstrated to correctly classify the objects despite differences in their speed and the location at which they cross the system.

Preliminary results from the Caribbean Acoustic Tracking Network (CATn): a data sharing partnership for acoustic tracking and movement ecology of marine animals in the Caribbean Sea

We have recently exchanged and integrated into a single database tag detections for conch, teleost and elasmobranch fish from four separately maintained arrays in the U.S. Virgin Islands including the NMFS queen conch array (St. John nearshore), NOAA’s Biogeography Branch array (St. John nearshore & midshelf reef); UVI shelf edge arrays (Marine Conservation District, Grammanik & other shelf edge); NOAA NMFS Apex Predator array COASTSPAN (St. John nearshore). The integrated database has over 7.5 million hits. Data is shared only with consent of partners and full acknowledgements. Thus, the summary of integrated data here uses data from NOAA and UVI arrays under a cooperative agreement. The benefits of combining and sharing data have included increasing the total area of detection resulting in an understanding of broader scale connectivity than would have been possible with a single array. Partnering has also been cost-effectiveness through sharing of field work, staff time and equipment and exchanges of knowledge and experience across the network. Use of multiple arrays has also helped in optimizing the design of arrays when additional receivers are deployed. The combined arrays have made the USVI network one of the most extensive acoustic arrays in the world with a total of 150+ receivers available, although not necessarily all deployed at all times. Currently, two UVI graduate student projects are using acoustic array data.

MCMC-based tracking and identification of leaders in groups

We present a novel framework for identifying and tracking dominant agents in groups. Our proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in shaping the system's collective behaviour based exclusively on the agents' observed trajectories. Further, the reasoning paradigm is made robust to multiple emissions and clutter by employing a class of recently introduced Markov chain Monte Carlo-based group tracking methods. Examples are provided that demonstrate the strong potential of the proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds. © 2011 IEEE.

Monte Carlo-Based Bayesian group object tracking and causal reasoning

We present algorithms for tracking and reasoning of local traits in the subsystem level based on the observed emergent behavior of multiple coordinated groups in potentially cluttered environments. Our proposed Bayesian inference schemes, which are primarily based on (Markov chain) Monte Carlo sequential methods, include: 1) an evolving network-based multiple object tracking algorithm that is capable of categorizing objects into groups, 2) a multiple cluster tracking algorithm for dealing with prohibitively large number of objects, and 3) a causality inference framework for identifying dominant agents based exclusively on their observed trajectories.We use these as building blocks for developing a unified tracking and behavioral reasoning paradigm. Both synthetic and realistic examples are provided for demonstrating the derived concepts. © 2013 Springer-Verlag Berlin Heidelberg.