A dendritic cell mechanism for detection, identification, and evaluation of aircraft failures

Azzawi, Dia Al; Perhinschi, Mario G.; Moncayo, Hever; Perez, Andres

doi:10.1016/j.conengprac.2015.04.010

Cited by 8 publications

(2 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Artificial Immune Systems-which are imitative mechanisms of vital actions of discrimination between self and nonself-have been proposed since 1990s. And a lot of methods have been proposed using various parts of artificial immune systems, for example, pattern recognition by B-cells for fault detection in gas lift oil well by Aguilar [2,3], Natural Killer (NK) immune cells mechanisms by Laurentys [4], clonal selection algorithm for maintenance scheduling of power generators by El-sharkh [5], dendritic cell for failure detection of aircraft by Azzawi [6]. Also lots of applications have been proposed-Wada et al [7] proposed an fault mode detection method for automotive exhaust gas treatment system, Inomo et al [8] proposed an failure diagnosis method for water supply network by using immune system.…”

Section: Introductionmentioning

confidence: 99%

Agent Based Fault Detection System for Chemical Processes using Negative Selection Algorithm

Kimura

Takeda

Tsuge

2018

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Recently, the number of industrial accidents of chemical plants has been increasing in Japan. The fault detection system is required to keep chemical plant safely. In this study, a fault detection system for a chemical plants using agent framework and negative selection algorithm was proposed. The negative selection algorithm is one of artificial immune systems. The artificial immune system is an imitative mechanism of vital actions to discriminate self/nonself to protect itself. The method was implemented and applied to a complicated chemical plant-which is a boiler plant virtually operated using a dynamic plant simulator. The simulations of fault detection were carried out. And also the results of simulations are presented in this paper.

show abstract

Section: Introductionmentioning

confidence: 99%

Agent Based Fault Detection System for Chemical Processes using Negative Selection Algorithm

Kimura

Takeda

Tsuge

2018

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

show abstract

“…The Dendritic Cell Algorithm has been used primarily in problems involving machine learning and classification [76] and fault and anomaly detection [77,78] specifically in power system monitoring [79]. This algorithm has proven effective in detection, identification, and evaluation of abnormal conditions affecting actuators, closed-loop sensors, structural components, and the propulsion system through simulation [80,81].…”

Section: Ais Techniquesmentioning

confidence: 99%

Artificial Immune System for Unmanned Aerial Vehicle Abnormal Condition Detection and Identification

McLaughlin¹

View full text Add to dashboard Cite

A detection and identification scheme for abnormal conditions was developed for an unmanned aerial vehicle (UAV) based on the artificial immune system (AIS) paradigm. This technique involves establishing a body of data to represent normal conditions referred to as "self" and differentiating these conditions from abnormal conditions, referred to as "non-self". Data collected from simulation of the UAV attempting to autonomously fly a pre-decided trajectory were used to develop and test a scheme that was able to detect and identify aircraft sensor and actuator faults. These faults included aerodynamic control surface locks and damages and angular rate sensor biases. The method used to create the AIS is known as the partition of the universe approach. This approach differs from standard clustering approaches because the universe is divided into uniform partition clusters rather than clustering data using some clustering algorithm. It is simpler and requires less computational resources. This will be the first time that this approach has been applied for use in aerospace engineering. Data collected from nominal flights were used to define self partitions, and the non-self partitions were defined implicitly. The creation scheme is also discussed, involving all software used for simulation, as well as the process of creating the self and the logic behind the detection and identification schemes. The detection scheme was evaluated based on detection rate, detection time, and false alarms for flights under both normal and abnormal conditions. The failure identification scheme was assessed in terms of identification rate and time. Investigation of the proposed technique showed promising results for the cases explored with comparable performance with respect to clustering-based approaches and motivates further research and extension of the proposed methodology toward a more complete health management system.

show abstract

A new version of the deterministic dendritic cell algorithm based on numerical differential and immune response

Wen

Liang

2021

Applied Soft Computing

View full text Add to dashboard Cite

A dendritic cell mechanism for detection, identification, and evaluation of aircraft failures

Cited by 8 publications

References 33 publications

Agent Based Fault Detection System for Chemical Processes using Negative Selection Algorithm

Agent Based Fault Detection System for Chemical Processes using Negative Selection Algorithm

Artificial Immune System for Unmanned Aerial Vehicle Abnormal Condition Detection and Identification

A new version of the deterministic dendritic cell algorithm based on numerical differential and immune response

Contact Info

Product

Resources

About