A fast event detection algorithm for residential loads within normal and disturbed operating conditions

2016 ◽  
Vol 18 (1-2) ◽  
pp. 95-116 ◽  
Author(s):  
Faten MOUELHI
Keyword(s):  
Event Detection ◽  
Detection Algorithm ◽  
Operating Conditions

A phasor-distance based faulty phase detection and fault classification technique for parallel transmission lines

2020 ◽  
Vol 21 (4) ◽  
Author(s):  
Nishant Kothari ◽  
Bhavesh R. Bhalja ◽  
Vivek Pandya ◽  
Pushkar Tripathi ◽  
Soumitri Jena
Keyword(s):  
Transmission Lines ◽  
Power Flow ◽  
Detection Algorithm ◽  
Current Transformer ◽  
Operating Conditions ◽  
Fault Classification ◽  
Phase Detection ◽  
Parallel Transmission ◽  
Classification Technique ◽  
Computational Requirement

AbstractThis paper presents a phasor-distance based faulty phase detection and fault classification technique for parallel transmission lines. Detection and classification of faulty phase(s) have been carried out by deriving indices from the change in phasor values of current with a distance of one cycle. The derived indices have zero values during normal operating conditions whereas the index corresponding to the faulty phase exceeds the pre-defined threshold in case of occurrence of a fault. A separate ground detection algorithm has been utilized for the identification of involvement of ground in a faulty situation. The performance of the proposed technique has been evaluated for intra-circuit, inter-circuit and simultaneous faults with wide variations in system and fault conditions. The suggested technique has been evaluated for over 23,000 diversified simulated fault cases as well as 14 recorded real fault events. The performance of the proposed technique remains consistent under Current Transformer (CT) saturation as well as different amount and direction of power flow. Moreover, suitability to different power system network has also been studied. Also, faults having fault current less than pre-fault conditions have been detected accurately. The results obtained suggest that it is able to detect faulty phases as well as classify faults within quarter-cycle from the inception of fault with impeccable accuracy. Besides, as modern digital relays have been already equipped with phasor computation facility, phasor-based technique can be easily incorporated with relative ease. At last, a comparative evaluation suggests its superiority in terms of fault classification accuracy, fault detection time, diversify fault scenarios and computational requirement among other existing techniques.

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.

Development of a Torsional Behavior Powertrain Model for Multiple Misfire Detection

2005 ◽  
Author(s):  
Fabrizio Ponti
Keyword(s):  
Torsional Vibration ◽  
Engine Speed ◽  
Experimental Tests ◽  
Detection Algorithm ◽  
Operating Conditions ◽  
False Alarms ◽  
Time Interval ◽  
Short Time Interval ◽  
Torsional Behavior ◽  
Misfire Detection

Many methodologies have been developed in the past for misfire detection purposes based on the analysis of the instantaneous engine speed. The missing combustion is usually detected thanks to the sudden engine speed decrease that takes place after a misfire event. Misfire detection and in particular cylinder isolation is anyhow still a challenging issue for engines with a high number of cylinders, for engine operating conditions at low load or high engine speed and for multiple misfire events. When a misfire event takes place in fact a torsional vibration is excited and shows up in the instantaneous engine speed waveform. If a multiple misfire occurs this torsional vibration is excited more than once in a very short time interval. The interaction among these successive vibrations can generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation. The paper presents the development of a powertrain torsional behavior model in order to identify the effects of a misfire event on the instantaneous engine speed signal. The identified waveform has then been used to filter out the torsional vibration effects in order to enlighten the missing combustions even in the case of multiple misfire events. The model response is also used to quicken the setup process for the detection algorithm employed, evaluating before running specific experimental tests on a test bench facility, the values for the threshold and the optimal setup of the procedure. The proposed algorithm is developed in this paper for an SI L4 engine; Its application to other engine configurations is possible, as it is also discussed in the paper.

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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