A Hybrid Fault Event Detection Algorithm Using Fault Recorder Data

2010 ◽  
Author(s):  
Kang Taifeng ◽  
Wu Wenchuan ◽  
Sun Hongbin ◽  
Zhang Boming ◽  
Qian Xiao
Keyword(s):  
Event Detection ◽  
Detection Algorithm ◽  
Fault Recorder

A Satellite-linked Tag for the Long-term Monitoring of Diving Behavior in Large Whales

2021 ◽  
Author(s):  
Daniel M. Palacios ◽  
Ladd M. Irvine ◽  
Barbara A. Lagerquist ◽  
James A. Fahlbusch ◽  
John Calambokidis ◽  
...  
Keyword(s):  
Event Detection ◽  
Satellite Telemetry ◽  
Dive Depth ◽  
Detection Algorithm ◽  
Diving Behavior ◽  
Accelerometer Data ◽  
Precision Data ◽  
Geographic Ranges ◽  
Dive Behavior ◽  
Tracking Period

Abstract Despite spending much of their time on activities underwater, the technology in use to track whales over large geographic ranges via satellite has been largely limited to locational data, with most applications focusing on characterizing their horizontal movements. We describe the development of the RDW tag, a new Argos-based satellite telemetry device that incorporates sensors for monitoring the movements and dive behavior of large whales over several months without requiring recovery. Based on an implantable design, the tag features a saltwater conductivity switch, a tri-axial accelerometer, and an optional pressure transducer, along with onboard software for data processing and detection of behavioral events or activities of interest for transmission. We configured the software to detect dives and create per-dive summaries describing behavioral events associated with feeding activities in rorqual whales. We conducted a validation by proxy of the dive summary and event detection algorithms using data from a medium-duration archival tag. The dive summary algorithm accurately reported dive depth and duration, while the accuracy of the lunge-feeding event detection algorithm was dependent on the precision of the accelerometer data that was used, with a predicted accuracy of 0.74 for correctly classifying feeding dives from 1/64-G precision data and 0.95 from 1-mG precision data. We also present data from field deployments of the tag on seven humpback whales ( Megaptera novaeangliae ) and one blue whale ( Balaenoptera musculus ). The eight tags transmitted over a median tracking period of 17.5 d (range: 3.9-76.4 d) across both species. The median proportion of the tracking period summarized by received dives for the eight tags was 50.4% (range: 11.1-88.7%). The median number of received dives per day was 76.5 (range: 1-191). The results documented diel and longer-term variability in diving and feeding behavior, showing marked differences within and among individuals tracked contemporaneously. By monitoring the per-dive behavior of large whales over multi-month timescales of movement, the RDW tags provided some of the first assessments of previously unobservable behaviors across entire geographic ranges, linking local-scale behavior to broader, ecosystem-scale processes. The RDW tag extends the applications of whale satellite telemetry to new areas of physiology, ecology, and conservation.

scholarly journals Galerkin–Ivanov transformation for nonsmooth modeling of vibro-impacts in continuous structures

2020 ◽  
pp. 107754632094544
Author(s):  
Surya Samukham ◽  
S. N. Khaderi ◽  
C. P. Vyasarayani
Keyword(s):  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Numerical Integration ◽  
Event Detection ◽  
Applied Mathematics ◽  
Detection Algorithm ◽  
Jump Conditions ◽  
Unilateral Constraints ◽  
Velocity Jump ◽  
Impact Motion

This work deals with the modeling of nonsmooth vibro-impact motion of a continuous structure against a rigid distributed obstacle. Galerkin’s approach is used to approximate the solutions of the governing partial differential equations of the structure, which results in a system of ordinary differential equations. When these ordinary differential equations are subjected to unilateral constraints and velocity jump conditions, one must use an event detection algorithm to calculate the time of impact accurately. Event detection in the presence of multiple simultaneous impacts is a computationally demanding task. Ivanov (Ivanov A 1993 “Analytical methods in the theory of vibro-impact systems”. Journal of Applied Mathematics and Mechanics 57(2): pp. 221–236.) proposed a nonsmooth transformation for a vibro-impacting multi-degree-of-freedom system subjected to a single unilateral constraint. This transformation eliminates the unilateral constraints from the problem and, therefore, no event detection is required during numerical integration. This nonsmooth transformation leads to sign function nonlinearities in the equations of motion. However, they can be easily accounted for during numerical integration. Ivanov used his transformation to make analytical calculations for the stability and bifurcations of vibro-impacting motions; however, he did not explore its application for simulating distributed collisions in spatially continuous structures. We adopt Ivanov’s transformation to deal with multiple unilateral constraints in spatially continuous structures. Also, imposing the velocity jump conditions exactly in the modal coordinates is nontrivial and challenging. Therefore, in this work, we use a modal-physical transformation to convert the system from modal to physical coordinates on a spatially discretized grid. We then apply Ivanov’s transformation on the physical system to simulate the vibro-impact motion of the structure. The developed method is demonstrated by modeling the distributed collision of a nonlinear string against a rigid distributed surface. For validation, we compare our results with the well-known penalty approach.

scholarly journals A multiple pattern complex event detection scheme based on decomposition and merge sharing for massive event streams

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096133
Author(s):  
Jianhua Wang ◽  
Bang Ji ◽  
Feng Lin ◽  
Shilei Lu ◽  
Yubin Lan ◽  
...  
Keyword(s):  
Event Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Detection Scheme ◽  
Event Stream ◽  
Detection Model ◽  
Efficient Detection ◽  
High Efficient ◽  
Complex Events

Quickly detecting related primitive events for multiple complex events from massive event stream usually faces with a great challenge due to their single pattern characteristic of the existing complex event detection methods. Aiming to solve the problem, a multiple pattern complex event detection scheme based on decomposition and merge sharing is proposed in this article. The achievement of this article lies that we successfully use decomposition and merge sharing technology to realize the high-efficient detection for multiple complex events from massive event streams. Specially, in our scheme, we first use decomposition sharing technology to decompose pattern expressions into multiple subexpressions, which can provide many sharing opportunities for subexpressions. We then use merge sharing technology to construct a multiple pattern complex events by merging sharing all the same prefix, suffix, or subpattern into one based on the above decomposition results. As a result, our proposed detection method in this article can effectively solve the above problem. The experimental results show that the proposed detection method in this article outperforms some general detection methods in detection model and detection algorithm in multiple pattern complex event detection as a whole.

Automated event detection algorithm for two squatting protocols

2018 ◽  
Vol 59 ◽  
pp. 253-257 ◽  
Author(s):  
Wilshaw R. Stevens ◽  
Alicia Y. Kokoszka ◽  
Anthony M. Anderson ◽  
Kirsten Tulchin-Francis
Keyword(s):  
Event Detection ◽  
Detection Algorithm
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