An autonomic failure-detection algorithm

A mathematical model for the simulation of engine start-up thermodynamics has been developed and validated against engine test data. This numerical model has been validated using engine test results for both single and multiple combustor flameouts, and reasonable agreement between test and simulation data has been observed. Numerical simulations have then been generated for flameout cases that have not been available from engine tests, such as flame failure in different combinations of combustors, and at different engine operating conditions. The mathematical model features object modeling of engine components with three gas compositions, being air, fuel, and combustion products. The combustion system has been represented by six combustors, and the gas stream from each combustor has been divided according to the number of the gas path thermocouples downstream from the combustion system. The effects of heat transfer within the combustors and turbine have been modeled. Two sets of thermocouples have been considered, the first being thermocouples installed in multiple combustor burners, and the second being an array of thermocouple probes which are circumferentially positioned in the engine hot gas path. All thermocouples have been modeled as first order dynamic systems. The numerical simulations have been successfully used to support development of a new partial flame failure detection method, which is based on the combined measurements from both sets of thermocouples. A range of numerical simulations have been conducted in order to assess the ability of this new detection algorithm to detect different partial flame failure scenarios, and to examine the sensitivity of the detection algorithm with respect to thermocouples faults.

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Failure Detection Algorithm for Testing Dynamic Web Applications

International Journal of Computer and Communication Technology ◽

10.47893/ijcct.2017.1396 ◽

2017 ◽

pp. 37-41

Author(s):

J. Vijaya Sagar Reddy ◽

G. Ramesh

Keyword(s):

Web Sites ◽

Experimental Evaluation ◽

Web Application ◽

Web Applications ◽

Failure Detection ◽

Detection Algorithm ◽

The Internet ◽

Test Cases ◽

Dynamic Web ◽

The Web

Web applications are the most widely used software in the internet. When a web application is developed and deployed in the real environment, It is very severe if any bug found by the attacker or the customer or the owner of the web application. It is the very important to do the proper pre-analysis testing before the release. It is very costly thing if the proper testing of web application is not done at the development location and any bug found at the customer location. For web application testing the existing systems such as DART, Cute and EXE are available. These tools generate test cases by executing the web application on concrete user inputs. These tools are best suitable for testing static web sites and are not suitable for dynamic web applications. The existing systems needs user inputs for generating the test cases. It is most difficult thing for the human being to provide dynamic inputs for all the possible cases. This paper presents algorithms and implementation, and an experimental evaluation that revealed HTML Failures, Execution Failures, Includes in PHP Web applications.

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Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas

Journal of Diabetes Science and Technology ◽

10.1177/1932296818755173 ◽

2018 ◽

Vol 12 (3) ◽

pp. 599-607 ◽

Cited By ~ 11

Author(s):

Daniel P. Howsmon ◽

Nihat Baysal ◽

Bruce A. Buckingham ◽

Gregory P. Forlenza ◽

Trang T. Ly ◽

...

Keyword(s):

Real Time ◽

Artificial Pancreas ◽

Intervention Strategy ◽

Failure Detection ◽

Detection Algorithm ◽

Outpatient Setting ◽

False Positives ◽

Zone Model ◽

Infusion Site ◽

Detection Algorithms

Background: As evidence emerges that artificial pancreas systems improve clinical outcomes for patients with type 1 diabetes, the burden of this disease will hopefully begin to be alleviated for many patients and caregivers. However, reliance on automated insulin delivery potentially means patients will be slower to act when devices stop functioning appropriately. One such scenario involves an insulin infusion site failure, where the insulin that is recorded as delivered fails to affect the patient’s glucose as expected. Alerting patients to these events in real time would potentially reduce hyperglycemia and ketosis associated with infusion site failures. Methods: An infusion site failure detection algorithm was deployed in a randomized crossover study with artificial pancreas and sensor-augmented pump arms in an outpatient setting. Each arm lasted two weeks. Nineteen participants wore infusion sets for up to 7 days. Clinicians contacted patients to confirm infusion site failures detected by the algorithm and instructed on set replacement if failure was confirmed. Results: In real time and under zone model predictive control, the infusion site failure detection algorithm achieved a sensitivity of 88.0% (n = 25) while issuing only 0.22 false positives per day, compared with a sensitivity of 73.3% (n = 15) and 0.27 false positives per day in the SAP arm (as indicated by retrospective analysis). No association between intervention strategy and duration of infusion sets was observed ( P = .58). Conclusions: As patient burden is reduced by each generation of advanced diabetes technology, fault detection algorithms will help ensure that patients are alerted when they need to manually intervene. Clinical Trial Identifier: www.clinicaltrials.gov,NCT02773875

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The GLR failure detection algorithm for a class of nonlinear dynamic models with application to radar tracking problems

10.1109/irs.2008.4585759 ◽

2008 ◽

Cited By ~ 1

Author(s):

Dariusz Janczak ◽

Yury P. Grishin

Keyword(s):

Nonlinear Dynamic ◽

Dynamic Models ◽

Failure Detection ◽

Detection Algorithm ◽

Radar Tracking ◽

Nonlinear Dynamic Models

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