John Punwani

CHALLENGES IN CURRENT WIRELESS SENSOR TECHNOLOGY FOR RAILCAR STATUS MONITORING FOR NORTH AMERICA'S FREIGHT RAILROAD INDUSTRY

Ensuring rail safety is a priority for the Federal Railroad Administration (FRA) and the railroad industry in North America. One such endeavor is to leverage Wireless Sensor Networks (WSN) to monitor and report in real-time the status of mechanical and electrical components for each railcar, and in conjunction with other railroad subsystems, ensure the safety, security and integrity of transported goods.The envisioned solution utilizes sensors installed on each railcar to form a train-based wireless network and collect real-time (or near real-time) information on different elements of a train and transmit aggregated information to the locomotive, dispatch centers or regional offices for early fault detection and accident prevention. The railroads have been interested in using a standards-based low-cost communication protocol for this purpose, such as IEEE 802.15.4, often referred to as ZigBee.Our results show, however, that ZigBee was designed for smaller wireless networks, such as a single railcar. It exhibits several critical problems associated with the unique network topology found on a freight train and the size of such a network. In essence, the network would take the shape of a very long chain of nodes. Some of the problems stemming from this topology are excessively long synchronization delays for establishing the network along the entire train, severe problems with route discovery and maintenance necessary for selecting the next relay node along the chain, aggregation of data errors and a resulting unacceptable packet loss rate, the lack of a traffic prioritization mechanism to protect important packets such as those containing critical alarms of equipment failure, and many more.In this paper, we describe our findings and experiences in our evaluation of ZigBee for railcar monitoring onboard freight trains, a detailed analysis of the identified problems and their impact on the envisioned railcar monitoring as well as discuss potential solutions to these problems.Copyright

Hybrid Technology Networking: A Novel Wireless Networking Approach for Real-Time Railcar Status Monitoring

The North American freight railroad industry continuously strives towards improvements in the safety and security of freight transportation. One key effort focuses on the use of Wireless Sensor Networks (WSN) technologies to monitor and report mechanical and electrical component status for each railcar in real-time, as well as the status of the transported goods themselves. This allows real-time monitoring of railcar components such as air pressure, wheel bearing temperature, brake failure, wiring integrity, refrigeration unit failure, boxcar door opening, the detection of radioactive materials, dangerous substance leaks, and much more. The aggregated sensor data is transmitted to the locomotive, dispatch centers or regional offices for early fault detection and accident prevention.Our previous work [1] has shown that ZigBee technology based on the IEEE 802.15.4 faces numerous obstacles when applied to freight railcar monitoring. To address these problems our team proposed an alternate approach called Hybrid Technology Networking (HTN), which combines the benefits of ZigBee for low-power short-range communication and WiFi for high-performance long-distance communication between HTN sensor clusters.In this paper, we present our simulation results using our HTN protocol. We compare and discuss the performance of the ZigBee-only network environment with the proposed HTN and demonstrate the advantages offered by HTN. We also discuss our prototype sensor hardware platform using the HTN protocol and provide an outlook of the future work planned for HTN.© 2012 ASME

Performance Evaluation of Hybrid Technology Networking for Real-Time Monitoring in Freight Railroad Operations

Traditional Wireless Sensor Network (WSN) solutions have been deemed insufficient to address the requirements of freight railroad companies to implement real-time monitoring and control of their trains, tracks and wayside equipment. With only ZigBee-based elements, the transmission capabilities of WSN devices are limited in terms of coverage range and throughput. This leads to severe delay and congestion in the network, particularly in railroad scenarios that usually require the nodes to be arranged in linear chain-like topology. In such a multi-hop topology to communicate from one end of a train to the locomotive — and due to ZigBee’s limited communication range — data needs to be transmitted using a very high number of hops and thus generates long delays and congestion problems.To overcome this drawback, we have proposed a heterogeneous multi-hop networking approach called “Hybrid Technology Networking” (HTN). In HTN we combined Wireless Local Area Network (WLAN) technologies like WiFi, which provide improved communication range and higher data rates, with low-power communication technologies like ZigBee. This significantly reduces the number of hops required to deliver data across the network and hence solves the issues of delay and congestion, while also achieving superior enery efficiency and network lifetime. The sensor nodes are logically divided into clusters and each cluster has a WiFi “gateway”. All intra-cluster communication is achieved via IEEE 802.15.4 and ZigBee protocols, while all inter-cluster communication utilizes WiFi protocol standards.To implement our proposed technology in railroad networks, we are designing hardware prototypes and simulation models to evaluate the functionality and performance of our HTN solution, which is designed around a dual network stack design governed by the HTN protocol. This ensures full compliance with IEEE and industry communication protocols for interoperability. Since no simulation tools that seamlessly combine both WSN and WLAN technologies in a single module exist, we wrote our own simulation environment using OPNET. In this paper, we have provided information of implementing the HTN protocol in OPNET and the simulation results for different scenarios relevant to railroad operations. These results will demonstrate the efficacy of our proposed system as well as provide the baseline data for testing the hardware devices in live networks. Under simulated traffic and channel conditions and device configurations, we observed a decrease of 77.27% in end-to-end delay and an increase of 69.70% in received data volume when using HTN compared to ZigBee-only multi-hop networks, simulated over 14 railcars in railroad-relevant scenarios.Copyright

Performance modeling of a multi-tier multi-hop hybrid sensor network protocol

The North American railroad industry, with the objective of improving safety and security of their operations, have been exploring the possibilities of real-time monitoring and control of trains and wayside equipment. Wireless Sensor Networks (WSNs) have emerged as the de-facto solution for most measurement and monitoring operations. However, widely used commercial WSN solutions, like ZigBee, exhibit significant delay and traffic congestion problems due to their limited range, throughput and overall capabilities. To overcome this problem we proposed a multi-tier multi-hop heterogeneous network technology, called Hybrid Technology Networking (HTN). HTN is comprised of sensors equipped with multiple complementary radio technologies in which the sensors form a cluster and communicate within their own cluster using low-power communication. Each clusters gateway then utilizes WiFi or similar longer range technologies for inter-cluster communication. In this paper, we present the design of our HTN node representation in OPNET. Furthermore, we present a theoretical framework that accurately models the delay in the network and verify the model with simulation results. We also present relevant results that demonstrate its full functionality, and also explore the efficacy of such hybrid multi-tier multi-hop implementations.

Energy Analysis in Deploying Wireless Sensor Networks for On-Board Real-Time Railcar Status Monitoring

Wireless Sensor Networks have been a focus of research in the North American freight railroad industry to enable on-board real-time sensing of critical railcar parameters. Important railcar aspects like wheel bearing temperature, air pressure, brake failure, and the integrity of transported goods can then be monitored closely and reliably. This enables immediate preventive actions in case of impending failures and also enables trend analysis that can be used to fine-tune maintenance efforts on railcars. These measures increase the safety, efficiency, and dependability of freight railroad operations.In our previous work [1–3] we have presented our Hybrid Technology Networking (HTN) protocol. This protocol provides optimal network performance for railcar monitoring applications. We have also presented HTNMote, a hardware prototyping platform that implements HTN. A deployment of HTNMotes was conducted and evaluated at the TTCI facility in Pueblo, Colorado in the US. The results from our field tests confirm that this approach is an order of magnitude better in performance compared to solutions based on ZigBee alone.In such an application, energy considerations represent a key challenge. These sensors have no readily available continuous energy source, but are expected to operate for years in harsh conditions. Energy harvesting — from vibrations, temperature differences, or solar radiation — may provide a potential solution to the energy scarcity. This also mandates that the HTNMote hardware and HTN protocol both be as energy efficient as possible.In this paper we present detailed measurements of the energy consumed by the HTNMote in various operational situations that are encountered during their operation onboard freight railcars. We introduce an energy consumption model based on our analysis of the measurements. This model demonstrates the energy-efficiency of the HTNMote implementation.© 2015 ASME

HTNMote: A Hardware Platform for Wireless Real-Time Railcar Monitoring and its Performance Analysis

Real-time monitoring of various components of a railcar such as wheel bearing temperature, brake line status, integrity of transported goods and many more has become a key focus area of research for the North American freight railroad industry. The ability for timely detection of abnormalities and impending failures prevents costly accidents, the potential loss of life and damage to the environment. Monitoring also increases overall operational efficiency, reliability and safety of freight railroads.Wireless Sensor Networks (WSN) are an obvious choice for implementing such a monitoring scheme. The accumulated data from various sensors distributed throughout each railcar along the length of the train is transmitted wirelessly using multi-hop transmissions to the locomotive for alerting and monitoring. From there, this information is also transmitted to dispatch centers for further analysis and recording. ZigBee technology based on the IEEE 802.15.4 standard is a popular choice among WSN communication protocols, owing to its low cost and low power requirements. ZigBee performance degrades severely in the long chain-like topology characteristic of the railroad application environment. This effectively disqualifies ZigBee as a candidate technology for such railcar monitoring deployments.To overcome these issues with ZigBee deployments for freight train monitoring we developed our Hybrid Technology Networking (HTN) approach [5–7]. HTN leverages both ZigBee and Wi-Fi communication to achieve reliable communication along an entire freight train. Railcar monitoring nodes are grouped into smaller clusters, within which we utilize ZigBee for its low-power operation and report to each cluster’s gateway node. The gateway nodes of all the clusters on a train communicate using Wi-Fi, to benefit from the high throughput and long communication range. This tiered architecture also results in a drastic reduction in overall hop count for end-to-end communication.In this paper we present HTNMote, a hardware platform that we are developing and employing for real-world evaluation of the HTN protocol. We also present results from our field tests of the HTNMotes at the Transportation Technology Center (TTCI) facility in Pueblo, Colorado, operated by the US Association of American Railroads (AAR). The results show that the use of HTN improves performance of the network by at least an order of magnitude compared to a ZigBee-only network. This paper details the design of our HTNMote platform, present the test setup and results, as well as conduct an in-depth analysis of the obtained results as they relate to railroad operations.© 2014 ASME

Long-Haul Whole-Body Vibration Assessment of Locomotive Cabs

Locomotives produce vibrations and mechanical shocks from irregularities in the track, structural dynamics, the engines, the trucks, and train slack movement (Mansfield, 2005). The different directions of the irregularities give rise to car-body vibrations in multiple axes including the following:• longitudinal, or along the length of the train (x);• lateral, or the side-to-side direction of the train (y);• vertical (z).The structural dynamics of rail vehicles give rise to several resonances in the 0.5–20Hz frequency range (Andersson, et al., 2005). Resonances are frequencies in the locomotive that cause larger amplitude oscillations. At these frequencies, even small-amplitude input vibration can produce large output oscillations. Further exacerbating the vibration environment, coupling of the axes of movement occurs: Motions in one direction contribute to motion in a different direction. The magnitude of vertical vibration in rail vehicles is reportedly well below many other types of vehicles (Dupuis & Zerlett, 1986; Griffin, 1990; Johanning, 1998). However, a lack of data from long-haul freight operations prevents an adequate characterization of the vibration environment of locomotive cabs.The authors describe results from 2 long-haul whole-body vibration (WBV) studies collected on a 2009 GE ES44C4 locomotive and a 2008 EMD SD70ACe. These WBV studies sponsored by the Federal Railroad Administration (FRA) examined WBV and shock in locomotives over 123 hours and 2274 track miles. The researchers recorded vibration data using 2 triaxial accelerometers on the engineers’ seat: a seat pad accelerometer placed on the seat cushion and a frame accelerometer attached to the seat frame at the base. The research team collected and analyzed vibrations in accordance with ISO 2631-1 and ISO 2631-5. ISO 2631-1 defines methods for the measurement of periodic, random and transient WBV. The focus of ISO 2631-5 is to evaluate the exposure of a seated person to multiple mechanical shocks from seat pad measurements.Exposure to excessive vibration is associated with an increased occupational risk of fatigue-related musculoskeletal injury and disruption of the vestibular system. While this is not an established causal relationship, it is possible that vibration approaching the ISO 2631-1 health caution guidance zones may lead to an increased occupational risk.The results from these rides show that the frequency-weighted ISO 2631 metrics are below the established health guidance caution zones of the WBV ISO 2631 standards. The goals of these studies are to:• collect data in accordance with international standards so results can be compared with similar findings in the literature for shorter duration rides as well as vibration studies in other transportation modes,• to characterize vibration and shock in a representative sample of locomotive operations to be able to generalize the results across the industry, and• collect benchmark data for future locomotive cab ride-quality standards.Copyright

Heavy Haul Coal Car Wheel Load Environment: Rolling Contact Fatigue Investigation

Railway wheels and rails do not achieve full wear life expectancy due to the combination of wear, plastic deformation, and surface, subsurface, and deep subsurface cracks. Sixty-seven percent of wheel replacement and maintenance in North America is associated with tread damage [1].Spalling and shelling are the two major types of wheel tread damage observed in railroad operations. Spalling and slid flat defects occur due to skidded or sliding wheels caused by, in general, unreleased brakes. Tread shelling (surface or shallow subsurface fatigue) occurs due to cyclic normal and traction loads that can generate rolling contact fatigue (RCF). Shelling comprises about half of tread damage related wheel replacement and maintenance. The annual problem size associated with wheel tread RCF is estimated to be in the tens of millions of dollars. The total cost includes maintenance, replacement, train delays and fuel consumption.To study the conditions under which RCF damage accumulates, a 36-ton axle load aluminum body coal car was instrumented with a high accuracy instrumented wheelset (IWS), an unmanned data acquisition (UDAC) system, and a GPS receiver. This railcar was sent to coal service between a coal mine and power plant, and traveled approximately 1,300 miles in the fully loaded condition on each trip. Longitudinal, lateral, and vertical wheel-rail forces were recorded continuously during four loaded trips over the same route using the same railcar and instrumentation. The first two trips were conducted with non-steering 3-piece trucks and the last two trips were conducted with passive steering M-976 compliant trucks to allow comparison of the wheel load environment and RCF accumulation between the truck types. RCF initiation predictions were made using “Shakedown Theory” [2]. Conducting two trips with each set of trucks allowed for analysis of the effects of imbalance speed conditions (cant deficiency or excess cant) at some curves on which the operating speeds varied significantly between trips.Copyright

Performance analysis of adaptive clustering in Hybrid Technology Networking

North Americas railroad industry and the Federal Railroad Administration continuously strive to improve operational safety and security of their operations. In order to design a reliable and efficient real-time monitoring and control network for freight trains and railcars, we had previously proposed a novel approach called Hybrid Technology Networking (HTN). HTN deploys sensor nodes in clusters, with intra-cluster communication provided by ZigBee and inter-cluster communication accomplished via WiFi through dynamically assigned node roles called gateways. ZigBee provides HTN with low-power operations and WiFi enables long-range communication for high performance. Due to a complex working environment the network topology changes frequently, which often leads to poor resource utilization, reduced network lifetime, fluctuations in channel conditions, high latency in end-to-end data delivery and variable loading at the gateways. To resolve this problem, HTN provides for cluster adaptation. In this paper, we describe algorithms to merge and split HTN clusters for making them adaptive to changing operating scenarios. We also explore how the process of making clusters adaptive will affect latency and reliability in the network.

Measurement of Residual Stress in Railway Wheels With Vertical Split Rim Failures

Residual stresses are known to significantly impact the initiation and growth of cracks in metallic components such as railway wheels. Tensile residual stresses are of particular concern due to their ability to non-conservatively affect performance. Vertical split rim (VSR) is an important failure mode for railway wheels. Vertical split rim, like any crack growth failure mode, is significantly influenced by residual stress (e.g., mean or steady stress effects). The crack face of a typical VSR wheel shows signs of low-cycle fatigue. Recently, residual stress measurements were performed on a set of Class C railway wheels. This study looked at the difference in axial residual stress for wheels in three primary conditions: new (as manufactured), service-worn, and wheels that failed through VSR. Residual stresses were significantly larger in the service-worn condition and for wheels that had failed due to VSR relative to the new condition. There is a small difference in the axial residual stress profiles of wheels that failed due to VSR compared to other service-worn wheels. It is unclear, however, if the difference is significant based on a limited population of data. This paper provides a description of the methods used to quantify residual stress in the Class C railway wheels and presents important results from the study.Copyright