A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives

During the last decade, due to the increasing importance of reliability and availability, railway industry is making greater use of fault diagnosis approaches for early fault detection, as well as Condition-based maintenance frameworks. Due to the influence of traction drive in the railway system availability, several research works have been focused on Fault Diagnosis for Railway traction drives. Fault diagnosis approaches have been applied to electric machines, sensors and power electronics. Furthermore, Condition-based maintenance framework seems to reduce corrective and Time-based maintenance works in Railway Systems. However, there is not any publication that summarizes all the research works carried out in Fault diagnosis and Condition-based Maintenance frameworks for Railway Traction Drives. Thus, this review presents the development of Health Assessment and Fault Diagnosis in Railway Traction Drives during the last decade

A Review: Prognostics and Health Management in Automotive and Aerospace

Prognostics and Health Management (PHM) attracts increasing interest of many researchers due to its potentially important applications in diverse disciplines and industries. In general, PHM systems use real-time and historical state information of subsystems and components of the operating systems to provide actionable information, enabling intelligent decision-making for improved performance, safety, reliability, and maintainability. Every year, a substantial number of papers in this area including theory and practical applications, appear in academic journals, conference proceedings and technical reports. This paper aims to summarize and review researches, developments and recent contributions in PHM for automotive- and aerospace industries. It can also be considered as the starting point for researchers and practitioners in general to assist them through PHM implementation and help them to accomplish their work more easily.Algorithms and the Foundations of Software technolog

Design of a hydraulic servo-actuation fed by a regenerative braking system

Many conventional truck and working machines are equipped with additional hydraulic tooling or manipulation systems which are usually fed through a mechanical connection with the internal combustion engine, involving a poor efficiency. In particular, this is a common situation for industrial vehicles whose mission profiles involves a relevant consumption of energy by the on board hydraulic systems, respect to the one really needed for only traction purpose. In this work it is proposed an innovative solution based on the adoption of a system aimed to recover braking energy in order to feed an efficient on board hydraulic actuation system. The proposed system is then adopted to a real application, an Isuzu truck equipped with a hydraulic tooling for garbage collection. A prototype of the system has been designed, assembled and tested showing a relevant improvement of system efficiency and the feasibility of the proposed approach. In the paper the proposed solution is presented, showing the simulation models and preliminary validation results including experimental devices assembled to perform the tests

Condition monitoring of wind turbine pitch controller: A maintenance approach

With the increase of wind power capacity worldwide, researchers are focusing their attention on the operation and maintenance of wind turbines. A proper pitch controller must be designed to extend the life cycle of a wind turbine’s blades and tower. The pitch control system has two primaries, but conflicting, objectives: to maximize the wind energy captured and converted into electrical energy and to minimize fatigue and mechanical load. Four metrics have been proposed to balance these two objectives. Also, diverse pitch controller strategies are proposed in this paper to evaluate these objectives. This paper proposes a novel metrics approach to achieve the conflicting objectives with a maintenance focus. It uses a 100 kW wind turbine as a case study to simulate the proposed pitch control strategies and evaluate with the metrics proposed. The results are shown in two tables due to two different wind models are used

Mechatronics in Sustainable Mobility: Two Electric Vehicle Applications

In this paper, we first review the role that mechatronics and advanced control have in modern road vehicles, in particular their present and potential impact on sustainable mobility. We then illustrate this with two research examples. Firstly, we show how electronic science, control system techniques and computing manifest themselves in the design of an advanced battery management algorithm designed to estimate two unmeasurable but vital quantities, State of Charge (SoC) and State of Health (SoH): this allows better utilisation of battery capacity, with scope for advanced prognostics and diagnostics. Secondly, we show how multi-domain modelling integrating mechanical science and electronic science can be used to express component ageing as part of a set of vehicle-level performance objectives and used to explore the trade-offs between conflicting requirements, aiding sensible design choices

Model-based prognostics for energy-constrained mobile systems operating in stochastic environments

Due to development of novel and more efficient energy storage systems we bear witness to the dawn of a new era of mobile systems. They have become sophisticated in terms of hardware components and software applications which have made it possible to develop integrated solutions for a large number of imaginable applications ranging from electric vehicles all the way to fully autonomous systems operating in a wide variety of ecosystems, e.g., service, surveillance or bio-inspired robots. Generally it is expected that a mobile system exhibits a sufficient degree of autonomy in the sense of energy availability such that it at least accomplishes the mission objectives for which it is intended. Nevertheless, such autonomy, is influenced to a large extent by the remaining energy that can be retrieved from its energy storage system and by the environment conditions in which the system operates. Assessing the reliability of a mission requires using systems internal and external situational awareness to determine if the available energy at least meets the energy needs demanded by the future operation of the mobile system in order to determine its remaining useful life (RUL). Having this information as soon as possible may allow the decision maker to apply a contingency plan to intervene and reconfigure the mission execution strategy in order to improve the probability of success, in those situations in which the system becomes incapable of achieving the original mission objectives. Numerous studies have been published for assessing mission reliability and estimating the RUL of mobile systems. However, they deal with structured environment conditions and thus with relatively deterministic loads. Moreover, these approaches neglect the inherent uncertainty which stems from multiple sources such as the lack of knowledge about the true energy available in the mobile system, the noise introduced by sensors or the randomness of the operation environment, just to mention a few. The approach presented in this work is built around the belief that the RUL estimation is formulated as an uncertainty propagation problem. Accordingly, to estimate the RUL multiple sources of uncertainty involved in its estimation are first characterized and then propagated with the aim of computing their combined effect, expressed in terms of a probability density function. The approach developed here achieves this estimation in a Monte-Carlo fashion in which several RUL realizations are simulated in order to accurately estimate its entire probability distribution. The aim of this work is therefore devoted to develop a solution capable of estimating the RUL with application to energy-constrained mobile systems operating in stochastic environments

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

A framework development to predict remaining useful life of a gas turbine mechanical component

Power-by-the-hour is a performance based offering for delivering outstanding service to operators of civil aviation aircraft. Operators need to guarantee to minimise downtime, reduce service cost and ensure value for money which requires an innovative advanced technology for predictive maintenance. Predictability, availability and reliability of the engine offers better service for operators, and the need to estimate the expected component failure prior to failure occurrence requires a proactive approach to predict the remaining useful life of components within an assembly. This research offers a framework for component remaining useful life prediction using assembly level data. The thesis presents a critical analysis on literature identifying the Weibull method, statistical technique and data-driven methodology relating to remaining useful life prediction, which are used in this research. The AS-IS practice captures relevant information based on the investigation conducted in the aerospace industry. The analysis of maintenance cycles relates to the examination of high-level events for engine availability, whereby more communications with industry showcase a through-life performance timeline visualisation. Overhaul sequence and activities are presented to gain insights of the timeline visualisation. The thesis covers the framework development and application to gas turbine single stage assembly, repair and replacement of components in single stage assembly, and multiple stage assembly. The framework is demonstrated in aerospace engines and power generation engines. The framework developed enables and supports domain experts to quickly respond to, and prepare for maintenance and on-time delivery of spare parts. The results of the framework show the probability of failure based on a pair of error values using the corresponding Scale and Shape parameters. The probability of failure is transformed into the remaining useful life depicting a typical Weibull distribution. The resulting Weibull curves developed with three scenarios of the case shows there are components renewals, therefore, the remaining useful life of the components are established. The framework is validated and verified through a case study with three scenarios and also through expert judgement

Failure detection techniques on the demand side of smart and sustainable compressed air systems : a systematic review

The industrial sector is a crucial economic pillar, seeing annual increases in the production output. In the last few years, a greater emphasis has been placed on the efficient and sustainable use of resources within industry. The use of compressed air in this field is hence gaining interest. These systems have numerous benefits, such as relative low investment costs and reliability; however, they suffer from low-energy efficiency and are highly susceptible to faults. Conventional detection systems, such as ultrasonic leak detection, can be used to identify faults. However, these methods are time consuming, meaning that leakages are often left unattended, contributing to additional energy wastage. Studies published in this area often focus on the supply side rather than the demand side of pneumatic systems. This paper offers a novel review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology of fault detection methods on the demand side of compressed air systems, leading towards a comprehensive understanding of smart and sustainable pneumatic systems. Fifty-three studies were classified and reviewed under the following three areas: (a) demand parameters which help in identifying fault sources; (b) approaches taken to analyse the parametric data; and (c) the role of Artificial Intelligence (AI) in pneumatic fault monitoring systems. This review shows that fault detection on the demand side has received greater importance in the last five years and that data analysis is crucial for AI to be implemented correctly. Nevertheless, it is clear that further research in this sector is essential, in order to investigate more complex systems. It is envisaged that this study can promote the adoption of such systems, contributing to an energy-efficient and cost-effective industry.peer-reviewe