Integrating IVHM and Asset Design

Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable effective and efficient maintenance and operation of the target vehicle. It accounts for the collection of data, conducting analysis, and supporting the decision-making process for sustainment and operation. The design of IVHM systems endeavours to account for all causes of failure in a disciplined, systems engineering, manner. With industry striving to reduce through-life cost, IVHM is a powerful tool to give forewarning of impending failure and hence control over the outcome. Benefits have been realised from this approach across a number of different sectors but, hindering our ability to realise further benefit from this maturing technology, is the fact that IVHM is still treated as added on to the design of the asset, rather than being a sub-system in its own right, fully integrated with the asset design. The elevation and integration of IVHM in this way will enable architectures to be chosen that accommodate health ready sub-systems from the supply chain and design trade-offs to be made, to name but two major benefits. Barriers to IVHM being integrated with the asset design are examined in this paper. The paper presents progress in overcoming them, and suggests potential solutions for those that remain. It addresses the IVHM system design from a systems engineering perspective and the integration with the asset design will be described within an industrial design process

A review of physics-based models in prognostics: application to gears and bearings of rotating machinery

Health condition monitoring for rotating machinery has been developed for many years due to its potential to reduce the cost of the maintenance operations and increase availability. Covering aspects include sensors, signal processing, health assessment and decision-making. This article focuses on prognostics based on physics-based models. While the majority of the research in health condition monitoring focuses on data-driven techniques, physics-based techniques are particularly important if accuracy is a critical factor and testing is restricted. Moreover, the benefits of both approaches can be combined when data-driven and physics-based techniques are integrated. This article reviews the concept of physics-based models for prognostics. An overview of common failure modes of rotating machinery is provided along with the most relevant degradation mechanisms. The models available to represent these degradation mechanisms and their application for prognostics are discussed. Models that have not been applied to health condition monitoring, for example, wear due to metal–metal contact in hydrodynamic bearings, are also included due to its potential for health condition monitoring. The main contribution of this article is the identification of potential physics-based models for prognostics in rotating machinery

Integrating IVHM and asset design

Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable effective and efficient maintenance and operation of the target vehicle. It accounts for the collecting of data, conducting analysis, and supporting the decision-making process for sustainment and operation. The design of IVHM systems endeavours to account for all causes of failure in a disciplined, systems engineering, manner. With industry striving to reduce through-life cost, IVHM is a powerful tool to give forewarning of impending failure and hence control over the outcome. Benefits have been realised from this approach across a number of different sectors but, hindering our ability to realise further benefit from this maturing technology, is the fact that IVHM is still treated as added on to the design of the asset, rather than being a sub-system in its own right, fully integrated with the asset design. The elevation and integration of IVHM in this way will enable architectures to be chosen that accommodate health ready sub-systems from the supply chain and design trade-offs to be made, to name but two major benefits. Barriers to IVHM being integrated with the asset design are examined in this paper. The paper presents progress in overcoming them, and suggests potential solutions for those that remain. It addresses the IVHM system design from a systems engineering perspective and the integration with the asset design will be described within an industrial design process

Implementing IVHM on legacy aircraft: progress towards identifying an optimal combination of technologies

The aim of Integrated VehicleHealth Management(IVHM) is to improve the management of maintenance operations through the implementation of health monitoring tools on key components either by diagnosing deterioration or by estimating RemainingUseful Life(RUL) so as to effect timely, and cost effective, maintenance. Regarding the use of IVHM technology in legacy aircraft, one has to keep in mind that hardware modifications to improve the reliability of components is not normally considered a viable alternative to diagnostic and prognostic tools due to high certification costs. At the same time, the data and expertise gathered over years of operating the aircraft help to estimate much more accurately how different health monitoring tools could impact maintenance activities. Consequently, selecting the optimal combination of health monitoring tools for legacy aircraft is significantly easier than for a new design. While computer simulations of the maintenance process are essential to determine how different IVHM tools generate value for the stakeholders, it is not practicable to simulate all possible combinations in order to select which tools are to be installed. This paper describes a process to reduce their number of toolsets to be simulated starting with the identification of those components that present a higher potential to reduce maintenance costs and times in case their faults could be detected and/or predicted. This is followed by the definition of the minimum required accuracy of diagnostic and prognostic tools for each component. This enables designers to determine which tools—available or still being developed—can be implemented to achieve the expected improvement in maintenance operations. Different combinations of IVHM tools are then subjected to a preliminary risk and cost-benefit analysis. A significantly reduced number of combinations are then simulated to select the optimal blend of technologies

Model updating of a helicopter stub wing

In this paper we describe the process of optimization for the structural model of a helicopter stub-wing based on experimental data. The wing dynamics is updated using the ground vibration tests within the 0-80Hz frequency range and a detailed discussion is carried out to present the modeling errors and the specific finite element analysis leading to an improved dynamic behaviour. Because the main objective for model updating exercises of aeronautical structures is the prediction of the dynamic behavior in flight, as well as the effect of configuration changes, a set of in-flight measurements is determined with the objective to be used for the derivation of a representative model. A preliminary analysis of the model quality to be used subsequently in flight test conditions is carried out

A review of model based and data driven methods targeting hardware systems diagnostics

System health diagnosis serves as an underpinning enabler for enhanced safety and optimized maintenance tasks in complex assets. In the past four decades, a wide-range of diagnostic methods have been proposed, focusing either on system or component level. Currently, one of the most quickly emerging concepts within the diagnostic community is system level diagnostics. This approach targets in accurately detecting faults and suggesting to the maintainers a component to be replaced in order to restore the system to a healthy state. System level diagnostics is of great value to complex systems whose downtime due to faults is expensive. This paper aims to provide a comprehensive review of the most recent diagnostics approaches applied to hardware systems. The main objective of this paper is to introduce the concept of system level diagnostics and review and evaluate the collated approaches. In order to achieve this, a comprehensive review of the most recent diagnostic methods implemented for hardware systems or components is conducted, highlighting merits and shortfalls

Downtime uncertainty reduction through the correct implementation of health monitoring tools

The objective of Integrated Vehicle Health Management (IVHM) is to increase platform availability and reduce maintenance times and costs through the use of health monitoring on key systems. The information generated using condition monitoring algorithms can be used to reduce maintenance times, improve the management of the support process and operate the fleet more efficiently. This paper discusses the effect of advanced health monitoring tools on the uncertainty of predicted downtimes and costs for vehicles and fleets and how they affect the management of the asset. If a health monitoring tool is to be installed it is critical to keep in mind that the objective is to maximise the use of the asset, not just reduce the average downtime. An improvement of the availability might not translate in a significant increase of effective active time since operational planning normally involves working with conservative estimations for the maintenance time. Thus, algorithms that result in a higher average downtime but present lower uncertainty can be more effective at maximising the use of a given vehicle. Most Cost Benefit Analyses (CBAs) focus on calculating the difference between the current average downtime and the expected downtime to determine the benefit of using algorithms to diagnose or predict a fault. Calculating the variation of these uncertainties with the introduction of health monitoring tools is critical to assess what the real impact on the downtime is going to be. The benefits of the approach presented in this paper are: (1) a better understanding of how uncertainties play a role in the downtime and maintenance cost of the asset, (2) being able to differentiate between improving the availability of the asset and its active operational time and (3) an improvement in the viability of CBAs for health monitoring tools

A feasibility study on the implementation of visibility algorithms for fault diagnosis in aircraft fuel systems

This paper discusses the applicability of Visibility Algorithms to detect faults in condition monitoring applications. The general purpose of Visibility Algorithms is to transform time series into graphs and study them through the characterisation of their associated network. Degradation of a component results in changes to the network. This technique has been applied using a test rig of an aircraft fuel system to show that there is a correlation between the values of key metrics of visibility graphs and the severity of four failure modes. We compare the results of using Horizontal Visibility algorithms against Natural Visibility algorithms. The results also show how the Kullback-Leibler divergence and statistical entropy can be used to produce condition indicators. Experimental results show that there is little dispersion in the values of condition indicators, leading to a low probability of false positives and false negatives

Uncertainty of performance requirements for IVHM tools according to business targets

Organised jointly with the 6th European Workshop on Structural Health Monitoring 2012Operators and maintainers are faced with the task of selecting which health monitoring tools are to be acquired or developed in order to increase the availability and reduce operational costs of a vehicle. Since these decisions will affect the strength of the business case, choices must be based on a cost benefit analysis. The methodology presented here takes advantage of the historical maintenance data available for legacy platforms to determine the performance requirements for diagnostic and prognostic tools to achieve a certain reduction in maintenance costs and time. The effect of these tools on the maintenance process is studied using Event Tree Analysis, from which the equations are derived. However, many of the parameters included in the formulas are not constant and tend to vary randomly around a mean value (e.g.: shipping costs of parts, repair times), introducing uncertainties in the results. As a consequence the equations are modified to take into account the variance of all variables. Additionally, the reliability of the information generated using diagnostic and prognostic tools can be affected by multiple characteristics of the fault, which are never exactly the same, meaning the performance of these tools might not be constant either. To tackle this issue, formulas to determine the acceptable variance in the performance of a health monitoring tool are derived under the assumption that the variables considered follow Gaussian distributions. An example of the application of this methodology using synthetic data is included

Simulation of an aircraft environmental control system

The environmental control system of a civil aircraft is a major driver of maintenance. Legacy systems, such as those on the Boeing 737, are particularly at risk, as they are not instrumented for health management. These systems degrade in operation and allow compensation within their operation for degrading components, until severe degradation or failure results. The required maintenance is then both costly and disruptive. The goal of this research is to produce a simulation environment that can model the aircraft environmental control system, in order that analysis for sensor placement and algorithms can be performed without extensive, and expensive, testing. A simulation framework called Simscape Environmental Control System Simulation under All Conditions has been proposed and implemented. It offers a library of components that can be assembled into specific aircraft environmental control system simulation configurations. It is capable of simulating the health state indicating parameters at sub-system and component levels under a wide-range of aircraft operating scenarios. The developed framework has been successfully implemented to simulate a Boeing 737-800 passenger air conditioner. Its verification and validation has been carried out against the actual data corresponding to a Boeing 737-800 passenger air conditioner operating at two different cruise operating points. An extensive comparison of the simulation is presented against the data for all the passenger air conditioner components. The overall acquired results suggest that changes in the aircraft ambient conditions can have a noticeable impact on the demanded passenger air conditioner outlet temperature, and a substantial impact on the heat transfer in the primary and secondary heat exchangers. The reported simulation capability serves as a first step towards formulating an environmental control system fault simulation and diagnostic solution