The application of reasoning to aerospace Integrated Vehicle Health Management (IVHM): Challenges and opportunities

Ezhilarasu, Cordelia Mattuvarkuzhali; Skaf, Zakwan; Jennions, Ian K.

doi:10.1016/j.paerosci.2019.01.001

Cited by 69 publications

(38 citation statements)

References 40 publications

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“…In order to isolate the faults that propagate to other aircraft systems, the second method uses a hybrid combination of causal reasoning with ANFIS. Causal reasoning is a reasoning strategy that draws conclusions based on the cause and effect relationship of the concerned subjects [33]. In general, developing causal reasoning for a system such as EPS is a time-consuming and tedious task due to the large number of interactions between the EPS and other systems.…”

Section: Methods 2: the Fuzzy Boundary Approachmentioning

confidence: 99%

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

Ezhilarasu

Jennions

2020

Applied Sciences

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The Electrical Power System (EPS) in an aircraft is designed to interact extensively with other systems. With a growing trend towards more electric aircraft, the complexity of interactions between the EPS and other systems has grown. This has resulted in an increased necessity of implementing health monitoring methods like diagnosis and prognosis of the EPS at the systems level. This paper focuses on developing a diagnostic algorithm for the EPS to detect and isolate faults and their root causes that occur at the Line Replaceable Units (LRUs) connecting with aircraft systems like the engine and the fuel system. This paper aims to achieve this in two steps: (i) developing an EPS digital twin and presenting the simulation results for both healthy and fault scenarios, (ii) developing an Adaptive Neuro-Fuzzy Inference System (ANFIS) monitor to detect faults in the EPS. The results from the ANFIS monitor are processed in two methods: (i) a crisp boundary approach, and (ii) a fuzzy boundary approach. The former approach has a poor misclassification rate; hence the latter method is chosen to combine with causal reasoning for isolating root causes of these interacting faults. The results from both these methods are presented through examples in this paper.

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Section: Methods 2: the Fuzzy Boundary Approachmentioning

confidence: 99%

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

Ezhilarasu

Jennions

2020

Applied Sciences

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“…The available sensors, data concentrators and actuators establish a connection between the physical world and the cyber network. Specifically, the cyber-physical design and integration will give support for the physical world, such as monitoring of concurrent events, asset health monitoring and prognostics [74], which suggests data-driven approaches for modeling the quality measures of the aircraft, for example, reliability and maintainability, for understanding the dynamic interactions between different components in the DIMA architecture from a statistical view [75]. Powerful machine learning techniques can be leveraged to build the models and learn the association of components for predicting the failure rate and MTTR accurately [76], particularly with deep learning [77].…”

Section: Cyber-physical Integration Towards Intelligencementioning

confidence: 99%

A Survey of Optimal Hardware and Software Mapping for Distributed Integrated Modular Avionics Systems

et al. 2020

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With an increasing number of aircraft systems, a fully manual developmental approach is impractical for finding optimal hardware and software mapping from overwhelming configurations for Distributed Integrated Modular Avionics (DIMA) systems. The automation of finding such optimized mapping should be available and thoroughly understood. This paper is an investigation on the foundations of optimal hardware and software mapping for DIMA. We begin by reviewing the DIMA system architecture. Following that, we present the problem statement of hardware and software mapping and its ensuring mathematical optimization models. A set of primary architectural quality metrics (e.g., reliability and scalability) and aircraft constraints (e.g., segregation and resource constraints) are identified, which can be used to compose an objective function or compare and trade alternatives. Based on the quality metrics and aircraft constraints, we synthesize an encompassing formulation by means of multi-objective optimization. Various optimization approaches for hardware and software mapping are then reviewed and compared. Case studies of DIMA optimization are presented for avionics systems, in which running time is reported for different optimization problems with different objectives and constraints. In addition, we present and discuss open issues and future trends, from which future developments may draw upon.

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“…Machine learning and Artificial Intelligence (AI): The advancement in sensors and the increased amount of data generated resulted in rekindling of machine learning techniques and AI from the past decades to complement the current technologies [6]. The input domain knowledge required by the DT, to be in line with the system's performance, can be in the form of rules, ontologies, procedures, models or even sensor data [6], depending on the compatibility with the DT model. The output is generated by the DT model with the help of reasoning systems built around it and the advanced machine learning algorithms used.…”

Section: Enabling Technologiesmentioning

confidence: 99%

“…This results in saving time and cost involved due to unplanned downtime, and increases the availability of the vehicle. A fully functional IVHM system assists in acquiring and analyzing health data of a vehicle to optimize the suitable maintenance plans for CBM [6].…”

Section: Introductionmentioning

confidence: 99%

“…Later, it expanded to other vehicles like aircraft and ships and evolved as a paradigm-shift to support Condition-Based Maintenance (CBM) of the vehicles. IVHM aims to ensure that the host system functions as intended, without any unexpected failure [6]. With the help of IVHM systems, the maintenance cost can be brought down significantly by predicting the system health in advance and supporting CBM.…”

Section: Introductionmentioning

confidence: 99%

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Understanding the role of a Digital Twin in Integrated Vehicle Health Management (IVHM)

Ezhilarasu

Skaf

Jennions

2019

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

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Integrated Vehicle Health Management (IVHM) aims to support Condition-Based Maintenance (CBM) by monitoring, diagnosing, and prognosing the health of the host system. One of the technologies required by IVHM to carry out its objectives is the means to emulate the functioning of the host system, and the concept of a Digital Twin (DT) was introduced in aerospace IVHM to represent the functioning of such a complex system. This paper aims to discuss the role played by DT in the field of IVHM. A DT is the virtual representation of any physical product, that is used to project the functioning of the product at a given instance. The DT is used across the lifecycle of any product, and its output can be customized depending upon the area of application. The DT is currently popular in industry because of the technologies like sensors, cloud computing, Internet of Things, machine learning, and advanced software, which enabled its development. This paper discusses what encompasses a DT, the technologies that support the DT, its applications across industries, and its development in academia. This paper also talks about how a DT can combine with IVHM technology to assess the health of complex systems like an aircraft. Lastly, this paper presents various challenges faced by industry during the implementation of a DT and some of the possible opportunities for future growth.

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The application of reasoning to aerospace Integrated Vehicle Health Management (IVHM): Challenges and opportunities

Cited by 69 publications

References 40 publications

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System

A Survey of Optimal Hardware and Software Mapping for Distributed Integrated Modular Avionics Systems

Understanding the role of a Digital Twin in Integrated Vehicle Health Management (IVHM)

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