A Real-Time Fault Early Warning Method for a High-Speed EMU Axle Box Bearing

An axle box bearing is one of the most important components of high-speed EMUs (electric multiple units), which runs at a very fast speed, suffers a heavy load, and operates under various complex working conditions. Once a bearing fault occurs, it not only has an enormous impact on the railway system, but also poses a threat to personal safety. Therefore, there is significant value in studying a real-time fault early warning of a high-speed EMU axle box bearing. However, to our best knowledge, there are three obvious defects in the existing fault early warning methods used for high-speed EMU axle box bearings: (1) these methods based on vibration are extremely mature, but there are no vibration sensors installed in high-speed EMU axle box because it will greatly increase the manufacturing cost; (2) a TADS (trackside acoustic device system) can effectively detect early failures, but only a portion of railways are equipped with such a facility; and (3) an EMU-ODS (electric multiple unit onboard detection system) has reported numerous untimely warnings, along with warnings of frequent occurrence being missed. Whereupon, a method is proposed to realize the fault early warning of an axle box bearing without installing a vibration sensor on the high-speed EMU in service, namely a MLSTM-iForest (multilayer long short-term memory–isolation forest). First, the time-series data of the temperature-related variables of the axle box bearing is used as the input of MLSTM to predict the axle box bearing temperature in the future. Then, the deviation index of the predicted axle box bearing temperature is calculated. Finally, the deviation index is input into an iForest algorithm for unsupervised classification to realize the fault early warning of an axle box bearing. Experimental results on high-speed EMU operation data sets demonstrated the availability and feasibility of the presented method toward achieving early fault warnings of a high-speed EMU axle box bearing

A holistic approach to remote condition monitoring for the accurate evaluation of railway infrastructure and rolling stock

The rail industry needs to address a number of important operational challenges in the foreseeable future. First of all, the safety of rail transport needs to be maintained at an absolute maximum matching the achievements of the European airline industry of zero fatalities. Secondly, promote sustainable growth to support increasing demand for both passenger and freight rail transport. Thirdly, support the implementation of measurable innovations and improvements that help increase capacity of current infrastructure through enhanced availability. Finally, maximise the environmentally benign character of railway transport through exploitation of novel technologies such as hydrogen trains and advanced electrification employing renewable energy sources. This project, primarily focused on the UK Rail infrastructure, investigated the benefits arising from a holistic approach in the application of Remote Condition Monitoring (RCM) as a critical means for the accurate, efficient, reliable and cost-effective evaluation of key railway infrastructure assets and rolling stock. This work involved the use of several techniques and innovative methodologies based primarily on Acoustic Emission (AE) and vibration analysis in order to address the evaluation requirements for different components of interest. The results obtained have been very promising and present rail infrastructure managers and rolling stock operators with new opportunities for improved and more reliable operations. This work has led to the instrumentation of multiple sites across the UK rail network enabling measurements to be carried out on various assets under actual operational conditions. At Cropredy an integrated high-frequency vibro-acoustic RCM system has successfully been installed on the Chiltern railway line on the way from London to Birmingham. This customised system has been fully operational since 2015 measuring more than 200 passenger and freight trains every day moving at speeds up to 100 miles per hour (MPH). Prior to the installation of the system at Cropredy a Certificate (PA05/06524) of Acceptance was issued by Network Rail which after being renewed recently is now valid until September 2021. The system is due for an upgrade in the following stage of development, employing wireless sensors and advanced energy harvesting devices which are being developed under a collaborative Engineering and Physical Sciences Research Council (EPSRC) project between Exeter and Birmingham Universities, Network Rail, Swiss Approval UK and Quatrro. The widespread implementation of the techniques and methodologies researched will give rise to significant potential impact with respect to the effectiveness of maintenance strategies, particularly in terms of cost efficiency, improved availability of railway assets and better planning of available resources. As modern rail transport moves towards 24-hour railway, the inspection, maintenance and track renewal and upgrade regime will need to be re-thought at a fundamental level. Effective RCM will be a key factor in realistically enabling true round the clock operations. The results presented in this thesis have been part of a six-year research effort with a clear focus on addressing the true industrial need. The findings of this work have led to a re-think within Network Rail regarding the new possibilities arising from the effective use of RCM in designing and implementing more efficient and cost-effective railway operations whilst helping reduce the cost. The use of autonomous sensing systems in the future will change the inspection and maintenance strategies currently used shifting towards a truly prognostic operational strategy

Monitoring railway track condition using inertial sensors on an in-service vehicle

Effective maintenance of railway track is critical for the safe operation of any railway network. Efficient maintenance may also result in economic benefits for rail operators. The work in this thesis looks into how an inexpensive measurement system could be fitted to in-service railway vehicles such as commuter trains, to provide a relatively high frequency of measurement on their routes of operation, when compared to dedicated measurement vehicles. This thesis describes how a prototype inertial measurement system was designed and built, and fitted to a commuter train operating in the region south of London, UK. Inertial data is processed to provide a vertical profile of the track. A novel use of a modified Bryson-Frazier filter is used to produce vertical profile datasets which are repeatable to within 0.2 mm. Profiles calculated from multiple passes of the same areas of track are compared to show track degradation. Methods of estimating track stiffness are developed using vertical geometry data from repeated passes of the same track sections at differing speeds. Some correlation to stiffness is shown through the results, but exact measurements were not possible. Finally, two case studies are presented which show findings at a bridge approach, and through two level crossings

Research on the System Safety Management in Urban Railway

Nowadays, rail transport has become one of the most widely utilised forms of transport thanks to its high safety level, large capacity, and cost-effectiveness. With the railway network's continuous development, including urban rail transit, one of the major areas of increasing attention and demand is ensuring safety or risk management in operation long-term remains for the whole life cycle by scientific tools, management of railway operation (Martani 2017), specifically in developed and developing countries like Vietnam. The situation in Vietnam demonstrates that the national mainline railway network has been built and operated entirely in a single narrow gauge (1000mm) since the previous century, with very few updates of manual operating technology. This significantly highlights that up to now, the conventional technique for managing the safety operation in general, and collision in particular, of the current Vietnamese railway system, including its subsystems, is only accident statistics which is not a scientific-based tool as the others like risk identify and analyse methods, risk mitigation…, that are already available in many countries. Accident management of Vietnam Railways is limited and responsible for accident statistics analysis to avoid and minimise the harm caused by phenomena that occur only after an accident. Statistical analysis of train accident case studies in Vietnam railway demonstrates that, because hazards and failures that could result in serious system occurrences (accidents and incidents) have not been identified, recorded, and evaluated to conduct safety-driven risk analysis using a well-suited assessment methodology, risk prevention and control cannot be achieved. Not only is it hard to forecast and avoid events, but it may also raise the chance and amount of danger, as well as the severity of the later effects. As a result, Vietnam's railway system has a high number of accidents and failure rates. For example, Vietnam Rail-ways' mainline network accounted for approximately 200 railway accidents in 2018, a 3% increase over the previous year, including 163 collisions between trains and road vehicles/persons, resulting in more than 100 fatalities and more than 150 casualties; 16 accidents, including almost derailments, the signal passed at danger… without fatality or casual-ty, but significant damage to rolling stock and track infrastructure (VR 2021). Focusing and developing a new standardised framework for safety management and availability of railway operation in Vietnam is required in view of the rapid development of rail urban transport in the country in recent years (VmoT 2016; VmoT 2018). UMRT Line HN2A in southwest Hanoi is the country's first elevated light rail transit line, which was completed and officially put into revenue service in November 2021. This greatly highlights that up to the current date, the UMRT Line HN2A is the first and only railway line in Vietnam with operational safety assessment launched for the first time and long-term remains for the whole life cycle. The fact that the UMRT Hanoi has a large capacity, more complicated rolling stock and infrastructure equipment, as well as a modern communica-tion-based train control (CBTC) signalling system and automatic train driving without the need for operator intervention (Lindqvist 2006), are all advantages. Developing a compatible and integrated safety management system (SMS) for adaption to the safety operating requirements of this UMRT is an important major point of concern, and this should be proven. In actuality, the system acceptance and safety certification phase for Metro Line HN2A prolonged up to 2.5 years owing to the identification of difficulties with noncompliance to safety requirements resulting from inadequate SMS documents and risk assessment. These faults and hazards have developed during the manufacturing and execution of the project; it is impossible to go back in time to correct them, and it is also impossible to ignore the project without assuming responsibility for its management. At the time of completion, the HN2A metro line will have required an expenditure of up to $868 million, thus it is vital to create measures to prevent system failure and assure passenger safety. This dissertation has reviewed the methods to solve the aforementioned challenges and presented a solution blueprint to attain the European standard level of system safety in three-phase as in the following: • Phase 1: applicable for lines that are currently in operation, such as Metro Line HN2A. Focused on operational and maintenance procedures, as well as a training plan for railway personnel, in order to enhance human performance. Complete and update the risk assessment framework for Metro Line HN2A. The dissertation's findings are described in these applications. • Phase 2: applicable for lines that are currently in construction and manufacturing, such as Metro Line HN3, Line HN2, HCMC Line 1 and Line 2. Continue refining and enhancing engineering management methods introduced during Phase 1. On the basis of the risk assessment by manufacturers (Line HN3, HCMC Line 2 with European manufacturers) and the risk assessment framework described in Chapter 4, a risk management plan for each line will be developed. Building Accident database for risk assessment research and development. • Phase 3: applicable for lines that are currently in planning. Enhance safety requirements and life-cycle management. Building a proactive Safety Culture step by step for the railway industry. This material is implemented gradually throughout all three phases, beginning with the creation of the concept and concluding with an improvement in the attitude of railway personnel on the HN2A line. In addition to this overview, Chapters 4 through Chapter 9 of the dissertation include particular solutions for Risk assessment, Vehicle and Infrastructure Maintenance methods, Inci-dent Management procedures, and Safety Culture installation. This document focuses on constructing a system safety concept for railway personnel, providing stringent and scientific management practises to assure proper engineering conditions, to manage effectively the metro line system, and ensuring passenger safety in Hanoi's metro operatio

Size and Location Diagnosis of Rolling Bearing Faults: An Approach of Kernel Principal Component Analysis and Deep Belief Network

Diagnosing incipient faults of rotating machines is very important for reducing economic losses and avoiding accidents caused by faults. However, diagnoses of locations and sizes of incipient faults are very difficult in a noisy background. In this paper, we propose a fault diagnosis method that combines kernel principal component analysis (KPCA) and deep belief network (DBN) to detect sizes and locations of incipient faults on rolling bearings. Effective information of raw vibration signals processed by KPCA method is used as input signals of the DBN of which weights of the first RBM are initialized by contribution rates of principal components. A DBN with complex structures can be cut into a briefer network by KPCA-DBN model. That model reduces network structure and increases convergence rate. As a result, an average test accuracy by KPCA-DBN can reach 99.1% for identification of 12 labels including incipient faults and the training time is 28s which is half of that by DBN model. The average accuracy of rolling bearing location detection nearly gets to 100% and the average accuracy of fault size detection is above 99%. Compared with SVM, BP, CNN, Deep EMD-PCA (Empirical Mode Decomposition-Principal Component Analysis), CNN-SVM and DBN, it is found that training time can be shortened and detection accuracy can be improved by KPCA-DBN model. The proposed method is beneficial to realize sizes and locations detection of incipient faults online

Electronics in the on-line control of railway movements: quantitative aspects

The present thesis is concerned with a quantitative examination of the on-line control of railway movements and develops a mathematical technique for the evaluation of safety based on the use of Markov processes, illustrated with examples. In addition, the thesis presents a design methodology applicable to electronic safety systems. These systems are shown to be an essential element in the development of fully electronic railway signalling systems, as well as in the increased automation of railway movements. An analysis of the limits of automation of railway movements is described and discussed together with a possible system configuration for the achievement of crewless train operation. The research described herein has been carried out at the British Railways R & D division and the methods described have been successfully applied to real engineering problems. The industrial R & D background of the present thesis is also reflected in the inclusion of a section on the socio-economic consequences of major innovation, particularly in the field of automation and in the consideration of costs and benefits. Section 2 contains an approach evolved jointly with Mr. W.T. Parkman, also at the R & D Division of British Railways, and has been published as Reference 16. Section 5 is a short description or the work carried out by the group under the direct responsibility of the author at the R & D Division of British Railways

Applying simulation techniques to train railway traction drivers

The writer analyses the introduction of a simulator enabled approach to railway traction driver training and assesses whether the transition from a conventional training delivery process has been effective. The evaluation of effectiveness is based on a study of Iarnród Éireann’s simulator system. Evidence is contained within four supporting strands, i.e., the change in relevant operational risk that has been calculated using ex ante and ex post runs of Iarnród Éireann’s risk model, the internal rate of return on the financial investment necessary to effect the change, the results of an operator attitudinal study and the findings of an independent expert audit. The study establishes that simulation is an effective training medium. The attributes of the system and the use cases that resulted in this finding are described. The writer also presents additional value-adding training objectives that could increase the project’s internal rate of return or IRR. The study affirms that the required verisimilitude of a simulator system is a function of the training goals and the nature of the skills under development. Design features and use strategies can mitigate for potential negative effects of simulator operation. The findings have industry-wide relevance for those tasked with providing effective training to the 133,000 train drivers within the European Union

Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures

In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools

Using Bayesian networks to represent parameterised risk models for the UK railways

PhDThe techniques currently used to model risk and manage the safety of the UK railway network are not aligned to the mechanism by which catastrophic accidents occur in this industry. In this thesis, a new risk modelling method is proposed to resolve this problem. Catastrophic accidents can occur as the result of multiple failures occurring to all of the various defences put in place to prevent them. The UK railway industry is prone to this mechanism of accident occurrence, as many different technical, operational and organizational defences are used to prevent accidents. The railway network exists over a wide geographic area, with similar accidents possible at many different locations. The risk from these accidents is extremely variable and depends on the underlying conditions at each particular location, such as the state of assets or the speed of trains. When unfavourable conditions coincide the probability of multiple failures of planned defences increases and a 'risk hotspot' arises. Ideal requirements for modelling risk are proposed, taking account of the need to manage multiple defences of conceptually different type and the existence of risk hotspots. The requirements are not met by current risk modelling techniques although some of the requirements have been addressed experimentally, and in other industries and countries. It is proposed to meet these requirements using Bayesian Networks to supplement and extend fault and event tree analysis, the traditional techniques used for risk modelling in the UK railway industry. Application of the method is demonstrated using a case study: the building of a model of derailment risk on the UK railway network. The proposed method provides a means of better integrating industry wide analysis and risk modelling with the safety management tasks and safety related decisions that are undertaken by safety managers in the industry

Development of a model for smart card based access control in multi-user, multi-resource, multi-level access systems

The primary focus of this research is an examination of the issues involved in the granting of access in an environment characterised by multiple users, multiple resources and multiple levels of access permission. Increasing levels of complexity in automotive systems provides opportunities for improving the integration and efficiency of the services provided to the operator. The vehicle lease / hire environment provided a basis for evaluating conditional access to distributed, mobile assets where the principal medium for operating in this environment is the Smart Card. The application of Smart Cards to existing vehicle management systems requires control of access to motor vehicles, control of vehicle operating parameters and secure storage of operating information. The issues addressed include examination of the characteristics of the operating environment, development of a model and design, simulation and evaluation of a multiple application Smart Card. The functions provided by the card include identification and authentication, secure hash and encryption functions which may be applied, in general, to a wide range of access problems. Evaluation of the algorithms implemented indicate that the Smart Card design may be provably secure under single use conditions and conditionally secure under multiple use conditions. The simulation of the card design provided data to support further research and shows the design is practical and able to be implemented on current Smart Card types