Edward Stewart

Perspectives on railway track geometry condition monitoring from in-service railway vehicles

This paper presents a view of the current state of monitoring track geometry condition from in-service vehicles. It considers technology used to provide condition monitoring; some issues of processing and the determination of location; how things have evolved over the past decade; and what is being, or could/should be done in future research. Monitoring railway track geometry from an in-service vehicle is an attractive proposition that has become a reality in the past decade. However, this is only the beginning. Seeing the same track over and over again provides an opportunity for observing track geometry degradation that can potentially be used to inform maintenance decisions. Furthermore, it is possible to extend the use of track condition information to identify if maintenance is effective, and to monitor the degradation of individual faults such as dipped joints. There are full unattended track geometry measurement systems running on in-service vehicles in the UK and elsewhere around the world, feeding their geometry measurements into large databases. These data can be retrieved, but little is currently done with the data other than the generation of reports of track geometry that exceeds predefined thresholds. There are examples of simpler systems that measure some track geometry parameters more or less directly and accurately, but forego parameters such as gauge. Additionally, there are experimental systems that use mathematics and models to infer track geometry using data from sensors placed on an in-service vehicle. Finally, there are systems that do not claim to measure track geometry, but monitor some other quantity such as ride quality or bogie acceleration to infer poor track geometry without explicitly measuring it.

Enhanced fault diagnosis of roller bearing elements using a combination of empirical mode decomposition and minimum entropy deconvolution

This paper introduces a new signal processing algorithm for vibration-based fault detection and diagnosis of roller bearings. The methodology proposed in this paper is based on the combination of two data-adaptive techniques which are further enhanced through the use of an automatic feature identification mechanism. The new technique, introduced as empirical mode envelope with minimum entropy, combines elements from the empirical mode decomposition (EMD) and minimum entropy deconvolution (MED) approaches with an energy moment technique to improve the feature selection stage of the EMD algorithm. This improvement allows the processing chain to identify early stage roller bearing faults in noisier signals. The energy moment technique is used to automatically identify the most appropriate intrinsic mode function from the EMD process prior to the MED algorithm being applied. This is in contrast to conventional approaches which tend to use the first mode or make selections based on traditional energy techniques. The combination of the adaptive techniques of EMD and MED allows the development of an improved technique for fault detection and diagnosis of signals. Combining these techniques with the energy moment approach allows further improved fault detection in complex non-stationary conditions. The processing chain has been tested using data obtained during laboratory testing. From the experimental results, it is shown that the new technique is capable of the detection of early stage (minor) roller and outer race defects found in tapered-roller-bearings rotating at a variety of speeds and noise scenarios.

Modeling and Solving Real-Time Train Rescheduling Problems in Railway Bottleneck Sections

There usually exists a high density of traffic through bottleneck sections of mainline railways, where a perturbation of one single train could result in long consequential delays across a number of trains. In the event of disturbances, rescheduling trains approaching the bottleneck will be necessary to increase the throughput of the section. To model the real-time train rescheduling problems around bottleneck sections, a mixed-integer programming model is presented in this paper. An innovative improved algorithm (DE_JRM) is developed to solve the problem. The model and the algorithms are validated with a case study using Monte Carlo methodology, which demonstrates that the proposed algorithm can reduce the weighted average delay and satisfy the requirements of real-time traffic control applications.

Using Bogie-mounted Sensors to Understand the Dynamics of Third Rail Current Collection Systems

Electric railways collect power from the infrastructure via various current collection systems. For high-voltage AC- and DC-powered railways, this is usually achieved using overhead electrification equipment and a train-borne pantograph. The dynamics of such systems are well understood, and the systems are able to be operated under a range of conditions and speeds. Lower-voltage DC-powered railways (<1500 V) use a current collecting shoe as part of a shoegear system and track side electrification infrastructure in the form of a conductor rail. The dynamics of such systems are equally as complex as those of overhead systems. This is due to the interaction between the conductor rail and the track system, coupled with the dynamics of the conductor shoe assembly, which are mechanically linked with the bogie and axle systems. The systems also collect high currents (<2000 A), and therefore maintaining an effective electrical contact is essential. The interface between the conductor shoe and conductor rail is regulated through standards and guidelines. However, there are numerous engineering challenges in the effective management of the whole system that have yet to be addressed. The mechanical design of the system must balance the requirements of good fatigue life with appropriate impact strength. Other issues such as removal of contaminants from the conductor rail surface and shoe wear also have an impact on the design. This article presents some experimental results from a bogie-mounted instrumentation system designed to monitor a typical example of a shoegear assembly operated on the UK railway system. The results indicate that the shoegear broadly performs in accordance with the design guidelines. Several points of loss of contact were observed, and it is shown that the contact force between the conductor shoe and rail can be estimated. The mean force was found to vary with third rail height, but a wide distribution of forces is found at any one height because of hysteresis in the shoegear. Large, but short-term, forces and torques occur because of third rail irregularities and ramps.

Observations of train control performance on a camshaft-operated DC electrical multiple unit

In order to reduce energy consumption on DC railways where regenerative braking is not available, train control strategy or ‘driver style’ is a practical alternative. In 2011, instrumentation to monitor energy consumption on the Merseyrail network was fitted to a British Rail Class 508 DC camshaft-operated electrical multiple unit. In this paper, seven services from Hunts Cross to Southport are highlighted to demonstrate a number of driver styles and their correlation with energy consumption. The differences in energy consumption were observed to be related to driver aggression in both the acceleration and deceleration phases.

Development and design of a narrow-gauge hydrogen-hybrid locomotive

Hydrogen used as an energy carrier is a promising alternative to diesel for autonomous railway motive power, but, globally, few prototypes exist. In 2012, the Institution of Mechanical Engineers held the inaugural Railway Challenge, in which the participating teams had to develop, design and construct a locomotive to run on 10.25 inch (260.35 mm) gauge track while meeting certain set design criteria as well as competing in operational challenges. The University of Birmingham Railway Challenge Team’s locomotive design is described in this paper. The vehicle is the UK’s first hydrogen-powered locomotive and is called Hydrogen Pioneer. The drive-system consists of a hydrogen tank, a 1.1 kW proton-exchange-membrane fuel cell stack, a 4.3 kWh battery pack and two 2.2 kW permanent-magnet traction motors. The development of the locomotive, from the original concept to the final design, and the design validation are all presented in this paper. The locomotive completed successfully all challenges through which the proof of the concept of a hydrogen-hybrid locomotive was established.

Condition monitoring of railway pantographs to achieve fault detection and fault diagnosis

Railway pantographs are used around the world for collecting electrical energy to power railway vehicles from the overhead catenary. Faults in the pantograph system degrade the quality of the contact between the pantograph and catenary and reduce the reliability of railway operations. To maintain the pantographs in a good working condition, regular inspection tasks are carried out at rolling stock depots. The current pantograph inspections, in general, are only effective for the detection of major faults, providing limited incipient fault detection or fault diagnosis capabilities. Condition monitoring of pantographs has the potential to improve pantograph performance and reduce maintenance costs. As a first step in the realisation of practical pantograph condition monitoring, a laboratory-based pantograph test rig has been developed to gain an understanding of pantograph dynamic behaviours, particularly when incipient faults are present. In the first work of this kind, dynamic response data have been acquired from a number of pantographs that have allowed fault detection and diagnosis algorithms to be developed and verified. Three tests have been developed: (i) a hysteresis test that uses different excitation speeds, (ii) a frequency response test that uses different excitation frequencies, and (iii) a novel changing gradient test. Verification tests indicate that the hysteresis test is effective in detecting and diagnosing pneumatic actuator and elbow joint faults. The frequency response test is able to monitor the overall degradation in the pantograph. The changing gradient test provides fault detection and diagnosis in the pantograph head suspension and pneumatic actuator. The test rig and fault detection and diagnosis algorithms are now being developed into a depot-based prototype together with a number of industrial partners.

Use of a 3D model to improve the performance of laser-based railway track inspection

In recent decades, 3D reconstruction techniques have been applied in an increasing number of areas such as virtual reality, robot navigation, medical imaging and architectural restoration of cultural relics. Most of the inspection techniques used in railway systems are, however, still implemented on a 2D basis. This is particularly true of track inspection due to its linear nature. Benefiting from the development of sensor technology and constantly improving processors, higher quality 3D model reconstructions are becoming possible which push the technology into more challenging areas. One such advancement is the use of 3D perceptual techniques in railway systems. This paper presents a novel 3D perceptual system, based on a low-cost 2D laser sensor, which has been developed for the detection and characterisation of physical surface defects in railway tracks. An innovative prototype system has been developed to capture and correlate the laser scan data; dedicated 3D data processing procedures have then been developed in the form of three specific defect-detection algorithms (depth gradient, face normal and face-normal gradient) which are applied to the 3D model. The system has been tested with rail samples in the laboratory and at the Long Marston Railway Test Track. The 3D models developed represent the external surface of the samples both laterally (2D slices) and longitudinally (3D model), and common surface defects can be detected and represented in 3D. The results demonstrate the feasibility of applying 3D reconstruction-based inspection techniques to railway systems.