Threshold Monitoring of Urea SCR Systems

2006 ◽  
Author(s):  
Kim Yong-Wha ◽  
Michiel Van Nieuwstadt
Keyword(s):  
Threshold Monitoring

scholarly journals Monitoring Wind Turbine Gearbox with Echo State Network Modeling and Dynamic Threshold Using SCADA Vibration Data

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 982 ◽  
Author(s):  
Xin Wu ◽  
Hong Wang ◽  
Guoqian Jiang ◽  
Ping Xie ◽  
Xiaoli Li
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Operating Conditions ◽  
Dynamic Threshold ◽  
Detection Accuracy ◽  
Echo State Network ◽  
Monitoring Method ◽  
Vibration Data ◽  
Static Monitoring ◽  
Threshold Monitoring

Health monitoring of wind turbine gearboxes has gained considerable attention as wind turbines become larger in size and move to more inaccessible locations. To improve the reliability, extend the lifetime of the turbines, and reduce the operation and maintenance cost caused by the gearbox faults, data-driven condition motoring techniques have been widely investigated, where various sensor monitoring data (such as power, temperature, and pressure, etc.) have been modeled and analyzed. However, wind turbines often work in complex and dynamic operating conditions, such as variable speeds and loads, thus the traditional static monitoring method relying on a certain fixed threshold will lead to unsatisfactory monitoring performance, typically high false alarms and missed detections. To address this issue, this paper proposes a reliable monitoring model for wind turbine gearboxes based on echo state network (ESN) modeling and the dynamic threshold scheme, with a focus on supervisory control and data acquisition (SCADA) vibration data. The aim of the proposed approach is to build the turbine normal behavior model only using normal SCADA vibration data, and then to analyze the unseen SCADA vibration data to detect potential faults based on the model residual evaluation and the dynamic threshold setting. To better capture temporal information inherent in monitored sensor data, the echo state network (ESN) is used to model the complex vibration data due to its simple and fast training ability and powerful learning capability. Additionally, a dynamic threshold monitoring scheme with a sliding window technique is designed to determine dynamic control limits to address the issue of the low detection accuracy and poor adaptability caused by the traditional static monitoring methods. The effectiveness of the proposed monitoring method is verified using the collected SCADA vibration data from a wind farm located at Inner Mongolia in China. The results demonstrated that the proposed method can achieve improved detection accuracy and reliability compared with the traditional static threshold monitoring method.

Optimized Seismic Threshold Monitoring - Part 2: Teleseismic Processing

2002 ◽  
Vol 159 (5) ◽  
pp. 989-1004 ◽  
Author(s):  
T. Kværna ◽  
F. Ringdal ◽  
J. Schweitzer ◽  
L. Taylor
Keyword(s):  
Threshold Monitoring

scholarly journals Continuous seismic threshold monitoring

1992 ◽  
Vol 111 (3) ◽  
pp. 505-514 ◽  
Author(s):  
Frode Ringdal ◽  
Tormod Kvaerna
Keyword(s):  
Threshold Monitoring

Reducing Communication Overhead in Threshold Monitoring with Arithmetic Aggregation

2009 ◽  
Author(s):  
Yuanqiang Huang ◽  
Yongjian Wan ◽  
Yinan Ren ◽  
BingHeng Yan ◽  
Zhongzhi Luan ◽  
...  
Keyword(s):  
Communication Overhead ◽  
Threshold Monitoring

Seismic threshold monitoring for continuous assessment of global detection capability

1999 ◽  
Vol 89 (4) ◽  
pp. 946-959 ◽  
Author(s):  
Tormod Kværna ◽  
Frode Ringdal
Keyword(s):  
Grid Point ◽  
Nuclear Test ◽  
Target Area ◽  
Detection Capability ◽  
Site Specific ◽  
Novaya Zemlya ◽  
Noise Characteristics ◽  
Aftershock Sequences ◽  
Threshold Monitoring ◽  
Station Site

Abstract Continuous seismic threshold monitoring is a technique that has been developed over the past several years to assess the upper magnitude limit of possible seismic events that might have occurred in a geographical target area. The method provides continuous time monitoring at a given confidence level. In this article we expand upon previous work to apply the method to a global network of seismic stations and give examples of applications from a prototype system that will be installed at the International Data Center for monitoring the Comprehensive Nuclear Test Ban Treaty. Using a global grid of 2562 geographical aiming points, we computed site-specific threshold traces for each grid point and applied spatial interpolation to obtain full global coverage. For each grid point, the procedure is in principle to “focus” the network by tuning the frequency filters and array beams using available information on signal and noise characteristics at each station-site combination. Standard global P-phase attenuation relationships and travel-time tables (IASP91) are used in this initial implementation, but the system lends itself easily to applying station-site-specific corrections (magnitudes, travel times, etc.) to each seismic phase. We give examples of two main types of applications based on data from a worldwide seismic network: (a) an estimated continuous global threshold level and (b) an estimated continuous global detection capability. The first application provides a continuous view of the global seismic “background field” as calculated from the station data, with the purpose of assessing the upper magnitude limit of any seismic event that might have occurred anywhere on Earth. The second application introduces detection thresholds for each station and provides a simplified estimate, continuously in time, of the n-station detection capability of the network. The latter approach naturally produces higher threshold values, with the difference typically being 0.5-1 magnitude unit. We show that both these approaches are useful especially during large earthquakes, where conventional capability maps based on statistical noise and signal models cannot be applied. In order to illustrate the usefulness of combining global monitoring with site-specific monitoring for areas of special interest, we consider a large earthquake aftershock sequence in Kamchatka and its effect on the threshold trace in a very different region (the Novaya Zemlya nuclear test site). We demonstrate that the effects of the aftershock signals on the thresholds calculated for Novaya Zemlya are modest, partly because of the emphasis on high-frequency signals. This indicates that threshold monitoring could provide significantly improved seismic monitoring during aftershock sequences compared with conventional methods, for which the large number of detected phases tends to saturate the phase association process.

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