Integrated performance monitoring, performance maintenance, and failure detection for photonic regenerators

Author(s):  
G. Lakshminarayana
Author(s):  
Daniel Bekana ◽  
Antoni Antoniev ◽  
Martin Zach ◽  
Jan Mareček

Predictive maintenance has gained wide acceptance as a cost cutting strategy and improve maintenance in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In many cases, it enables identification of a potential problem before a major repair is necessary and downtime during critical operations can be avoided.In this paper we analyzed the used motor oil and its remaining resource in agricultural machines.


Inventions ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 62
Author(s):  
Dimosthenis Kyriazis

The emergence of service-oriented architectures has driven the shift towards a service-oriented paradigm, which has been adopted in several application domains. The advent of cloud computing facilities and recently of edge computing environments has increased the aforementioned paradigm shift towards service provisioning. In this context, various “traditional” critical infrastructure components have turned to services, being deployed and managed on top of cloud and edge computing infrastructures. However, the latter poses a specific challenge: the services of the critical infrastructures within and across application verticals/domains (e.g., transportation, health, industrial venues, etc.) need to be continuously available with near-zero downtime. In this context, this paper presents an approach for high-performance monitoring and failure detection of critical infrastructure services that are deployed in virtualized environments. The failure detection framework consists of distributed agents (i.e., monitoring services) to ensure timely collection of monitoring data, while it is enhanced with a voting algorithm to minimize the case of false positives. The goal of the proposed approach is to detect failures in datacenters that support critical infrastructures by targeting both the acquisition of monitoring data in a performant way and the minimization of false positives in terms of potential failure detection. The specific approach is the baseline towards decision making and triggering of actions in runtime to ensure service high availability, given that it provides the required data for decision making on time with high accuracy.


2015 ◽  
Vol 18 (5) ◽  
pp. 728-738 ◽  
Author(s):  
Bilge Saruhan ◽  
Guillermo Cesar Mondragón Rodríguez ◽  
Azhar Ali Haidry ◽  
Ayhan Yüce ◽  
Sascha Heikens ◽  
...  

Author(s):  
Robert Holzworth ◽  
Walter Walejeski

Utilities need technology that is able to accurately estimate the performance and health of the power plant, and assess and optimize the plant’s current generation position for the purposes of generating accurate market pricing and operating cash-flows forecasts. The technology must be able to provide the utility with the required information to support robust power trading and risk management strategies, and ultimately increase the profitability of the business. This paper will address the utilization of integrated performance monitoring technologies to improve asset optimization at power generating facilities and report on the health of the power plant. Additionally, this paper will provide insight to some specific advanced monitoring technologies, how integration of the technologies can provide increased value for plant operations, and address the impact on key performance indicators that almost all utilities track, formally or informally. Case studies related to the technical information presented will also be presented.


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