Segmentation Tracking Research Articles

Spectral analysis of railway vehicle vertical vibration under normal operating conditions

ABSTRACTThis study focuses on railway vertical random vibration–based spectral analysis under normal operating conditions. Vibration acceleration measurements are acquired using sensors mounted on the car body, bogie frame, axle bearing, and primary suspension of an Athens Metro vehicle running without passengers on a straight track. Two distinct track segments and four speeds (50, 60, 70, 80 km/h) are considered. The analysis focuses on the 0–1000 Hz frequency range using data-based non-parametric and parametric spectral estimation methods. The results indicate good agreement of the methods, the prominence of the 5–170 Hz frequency range along with higher frequencies at around 300 Hz and in the range of 600–750 Hz on the car body and the bogie frame vibration, the relatively minor dependency of the dynamics on the track segment, but their significant dependence on train speed. Yet, resonant frequencies are affected to a lesser extent, with at least 20 of them appearing as prominent.

Simulation and Analysis for Error from Satellite Tracking Segment Anti-spoofing

Simulation and Analysis for Error from Satellite Tracking Segment Anti-spoofing

Morphological Feature Extraction Based on Multiview Images for Wear Debris Analysis in On-line Fluid Monitoring

ABSTRACTWear state is an important indicator of machinery operation condition that reveals whether faults have developed and maintenance should be scheduled. Among the available techniques, vision-based on-line monitoring of wear particles in the lubricant circuit is preferred, where three-dimensional particle characterizations can be obtained for wear mode analysis. This article presents the application of an imaging system that captures wear particles in lubricant flow and the development of image processing procedures for multiview feature extraction. In particular, a framework including background subtraction, object segmentation, and debris tracking was adopted. Particle features were then used in a comprehensive morphological description of wear debris. Experiments showed that the system is able to produce a feasible and reliable indication of wear debris characteristics for machine condition monitoring.

A novel approach to Hough Transform for implementation in fast triggers

Telescopes of position sensitive detectors are common layouts in charged particles tracking, and programmable logic devices, such as FPGAs, represent a viable choice for the real-time reconstruction of track segments in such detector arrays. A compact implementation of the Hough Transform for fast triggers in High Energy Physics, exploiting a parameter reduction method, is proposed, targeting the reduction of the needed storage or computing resources in current, or next future, state-of-the-art FPGA devices, while retaining high resolution over a wide range of track parameters. The proposed approach is compared to a Standard Hough Transform with particular emphasis on their application to muon detectors. In both cases, an original readout implementation is modeled.

Alternate Double Single Track Lines

The paper discusses the advantages and shortcomings of alternate double single track (ADST) lines with respect to double track lines for high speed lines. ADST lines consists of sequences of double and single track segments optimally selected in order to reduce the construction and maintenance costs of railway lines and to optimize the timetables used to satisfy a given demand. The single tracks are selected to coincide with expensive segments (tunnels and viaducts) and the double tracks are chosen to coincide with flat areas and only where they are necessary. At the same time, departure times are adjusted for trains to cross at the cheap double track segments. This alternative can be used for new lines and also for existing conventional lines where some new tracks are to be constructed to reduce travel time (increase speed). The ADST proposal is illustrated with some examples of both types (new lines and where conventional lines exist), including the Palencia-Santander, the Santiago-Valparaiso-Vina del Mar and the Dublin-Belfast lines, where very important reductions (90 %) are obtained, especially where a railway infrastructure already exist. DOI: http://dx.doi.org/10.4995/CIT2016.2016.3426

How does railroad track closure affect housing values? The case of Seoul, Korea

In December 2010, a 6.3 km track segment of the railroad that connects Seoul with Chuncheon was removed because an alternative railroad route was built to accommodate a new faster train. This railroad track segment had long been believed to reduce local housing values because of its disamenities such as noise, shaking, safety problems, and visual intrusion. In this study, we investigate the impact of this railroad track closure on local housing values in Seoul’s housing market. The results from our analysis show that the railroad closure actually increased local housing values. However, even 40 months after the closure, a negative price effect remained because of the sustained stigma of the areas. This study is one of the first to verify the conjecture that ground-level railroad closure actually increases local housing values. Many local governments in the Seoul metropolitan area suggest that converting ground-level railroad tracks into underground railroad tracks is necessary to eliminate disamenities. From the standpoint of the economic benefit valuation of this conversion project, the results from this study can be used to measure the economic benefit in terms of increased local housing prices more accurately. However, the finding that the negative effect sustained even after the closure indicates that it is hard to remove the negative perceptions of former railroad crossing areas.

Robust Vision-Based Relative-Localization Approach Using an RGB-Depth Camera and LiDAR Sensor Fusion

This paper describes a robust vision-based relative-localization approach for a moving target based on an RGB-depth (RGB-D) camera and sensor measurements from two-dimensional (2-D) light detection and ranging (LiDAR). With the proposed approach, a target’s three-dimensional (3-D) and 2-D position information is measured with an RGB-D camera and LiDAR sensor, respectively, to find the location of a target by incorporating visual-tracking algorithms, depth information of the structured light sensor, and a low-level vision-LiDAR fusion algorithm, e.g., extrinsic calibration. To produce 2-D location measurements, both visual- and depth-tracking approaches are introduced, utilizing an adaptive color-based particle filter (ACPF) (for visual tracking) and an interacting multiple-model (IMM) estimator with intermittent observations from depth-image segmentation (for depth image tracking). The 2-D LiDAR data enhance location measurements by replacing results from both visual and depth tracking; through this procedure, multiple LiDAR location measurements for a target are generated. To deal with these multiple-location measurements, we propose a modified track-to-track fusion scheme. The proposed approach shows robust localization results, even when one of the trackers fails. The proposed approach was compared to position data from a Vicon motion-capture system as the ground truth. The results of this evaluation demonstrate the superiority and robustness of the proposed approach.

Evaluating the potential of a rolling deflection measurement system to estimate track modulus

Over the past two decades, a rolling deflection measurement system aiming to continuously measure the track modulus has been under development at the University of Nebraska – Lincoln under the sponsorship of the Federal Railroad Administration. This system measures the relative vertical distance (referred to as Yrel) between the rail surface and the rail/wheel contact plane at a distance of 1.22 m from the nearest wheel to the sensor system. The aim of this study was to investigate the potential of using the Yrel measurement as an indicator of the track modulus for various rail foundation conditions. To meet this objective, a detailed finite element model capable of simulating moving loads and track modulus variation was developed. One of the unique contributions of this study is that it presents a comprehensive study of the Yrel–track modulus relationship by defining more realistic support conditions using discrete spring supports and by simulating the stochastic nature of the track modulus along a 160-m track length. The numerical model was employed to examine the accuracy of estimating the track modulus using the Yrel measurements when foundation stiffness is variable. Furthermore, the correlation between the statistical properties of the track modulus and Yrel was studied over different track segment lengths.

Three Principles for Optimal Pricing of Trackage Rights

Borrowing from the literature on optimal road pricing, this paper introduces three efficiency-based principles for setting track access fees. The fundamental principle is that track fees should be set as close as possible to optimal congestion tolls on a track segment. Since this procedure gives an incentive to keep capacity inefficiently low in order to increase congestion tolls, the second principle is that track fees be devoted to paying for track maintenance, the opportunity cost of land, and the amortization of plant and equipment installed on the track. The third principle is that track fees should be set by traffic and cost conditions on a line and should not vary with the identity of the user whose freight is hauled on the line; this third principle is designed to encourage efficient location and mode choice. The combination of these three principles has the promise of increased willingness to use rail logistics systems, the installation of an appropriate level of capacity on each line, and optimal routing and traffic levels throughout the rail system.

Infrastructure maintenance, regeneration and service quality economics: A rail example

This paper proposes a formalized framework for the joint economic optimization of continuous maintenance and periodic regeneration of rail transport infrastructure taking into account output consisting not only in traffic levels but also in track service quality. In contrast with much optimization work pertaining to spatially contiguous maintenance works, its principal economic emphasis and objective focus are centered on the optimal allocation of current maintenance and periodic renewal expenses, on their yearly distribution among large network partitions, and on infrastructure pricing. The model equations are based on very simple assumptions of infrastructure degradation laws and on a manager's objective function optimized through optimal control procedures. Equations are tested on national French rail track segment databases using Box–Cox transformations and match rail regeneration and maintenance practices prevailing in France. More generally, the paper makes a broad contribution to capital theory, on the optimal maintenance and renewal of equipment, and defines a method applicable not only to other transport infrastructure but to a wide range of capital goods, including housing, cars and industrial machines.

Modeling, calibration and validation of tractive performance for seafloor tracked trencher

Shear stress–displacement model is very important to evaluate the tractive performance of tracked vehicles. A test platform, where track segment shear test and plate load test can be performed in bentonite–water mixture, was built. Through analyzing existing literatures, two shear stress–displacement empirical models were selected to conduct verification tests for seafloor suitability. Test results indicate that the existing models may not be suitable for seafloor soil. To solve this problem, a new empirical model for saturated soft-plastic soil (SSP model) was proposed, and series shearing tests were carried out. Test results indicate that SSP model can describe mechanical behavior of track segment with good approximation in bentonite–water mixture. Through analyzing main external forces applied to test scaled model of seafloor tracked trencher, drawbar pull evaluation functions was deduced with SSP model; and drawbar pull tests were conducted to validate these functions. Test results indicate that drawbar pull evaluation functions was feasible and effective; from another side, this conclusion also proved that SSP model was effective.

Tractive performance evaluation of seafloor tracked trencher based on laboratory mechanical measurements

To evaluate the tractive performance of tracked trencher on seafloor surface, a new shear stress-displacement empirical model was proposed for saturated soft-plastic soil (SSP model). To validate the SSP model, a test platform, where track segment shear test can be performed in seafloor soil simulacrum (bentonite water mixture), was built. Series shear tests were carried out. Test results indicate that the SSP model can describe the mechanical behavior of track segment with good approximation in seafloor soil simulacrum. Through analyzing the main external forces applied to seafloor tracked trencher during the uniform linear trenching process, a drawbar pull prediction model was deduced with the SSP model. A tracked walking mechanism of the seafloor tracked trencher prototype was built, and verification tests were carried out. Test results indicate that this prediction model was feasible and effective; moreover, from another side, this conclusion also proved that the SSP model was effective.

Object Tracking by Color and Active Contour Models Segmentation

This work presents a novel approach for an object recognition and tracking system, here known as SRCCA (Software de Reconhecimento de Cor e Contorno Ativo or Active Contour and Color Recognizing Software) by using color recognition in the HSV color space and active contour models (ACM). The main innovations proposed makes use of the association of distinct techniques employed for object tracking and detection, as well as the elaboration of an open source software through the use of C++ programming language and OpenCV functions. To enhance the tracking efficiency for targets in motion, the video capturing device was controlled by two servomotors, enabling the target to be followed, in case it moves in the x- or y-axis. The final system was tested and presented robust and efficient tracking and contour segmentation capabilities for targets in motion, regardless of shape and size.

ENDOCARDIUM SEGMENTATION: AN APPROACH USING LOCAL CHAN VESE MODEL WITH RADIAL CHARGE FITTING CURVE

Wall tracking and Endocardium segmentation in Echocardiography images is a prime requirement for the diagnosis of major cardiac diseases. To avoid manual procedures of wall tracing and to provide a quantitative aid in the diagnosis procedure to the cardiologist, a new approach based on Local Chan Vese Model is proposed. The Model is based on curve evolution, local statistical function and level set method, and the accuracy of result is based on contour placement. This initial contour is generated through Radial Charge Fitting curve which is an auto generated curve based on Gauss Law. It is found that the inclusion of Radial Charge Fitting Curve with Local Chan Vese Model provides an accurate Endocardium Segmentation. The proposed method is compared with the Local Chan Vese Model with manual initial contours. It is proved that the proposed Local Chan Vese Model with Radial Charge Fitting Curve is performing accurate Endocardium Segmentation with minimal iterations.

The design and performance of a prototype water Cherenkov optical time-projection chamber

A first experimental test of tracking relativistic charged particles by ‘drifting’ Cherenkov photons in a water-based optical time-projection chamber (OTPC) has been performed at the Fermilab Test Beam Facility. The prototype OTPC detector consists of a 77cm long, 28cm diameter, 40kg cylindrical water mass instrumented with a combination of commercial 5.1×5.1cm2 micro-channel plate photo-multipliers (MCP-PMT) and 6.7×6.7cm2 mirrors. Five MCP-PMTs are installed in two columns along the OTPC cylinder in a small-angle stereo configuration. A mirror is mounted opposite each MCP-PMT on the inner surface of the detector cylinder, effectively increasing the photo-detection efficiency and providing a time-resolved image of the Cherenkov light on the opposing wall. Each MCP-PMT is coupled to an anode readout consisting of thirty 50Ω microstrips. A 180-channel data acquisition system digitizes the MCP-PMT signals on one end of the microstrips using the PSEC4 waveform sampling-and-digitizing chip operating at a sampling rate of 10.24Gigasamples-per-second. The single-ended microstrip readout determines the time and position of a photon arrival at the face of the MCP-PMT by recording both the direct signal and the pulse reflected from the unterminated far end of the strip. The detector was installed on the Fermilab MCenter secondary beam-line behind a steel absorber where the primary flux is multi-GeV muons. Approximately 80 Cherenkov photons are detected for a through-going muon track in a total event duration of ~2ns. By measuring the time-of-arrival and the position of individual photons at the surface of the detector to ≤100ps and a few mm, respectively, we have measured a spatial resolution of ~15mm for each MCP-PMT track segment, and, from linear fits over the entire track length of ~40cm, an angular resolution on the track direction of ~60mrad.

Sea surface height and dynamic topography of the ice‐covered oceans from CryoSat‐2: 2011–2014

AbstractWe examine 4 years (2011–2014) of sea surface heights (SSH) from CryoSat‐2 (CS‐2) over the ice‐covered Arctic and Southern Oceans. Results are from a procedure that identifies and determines the heights of sea surface returns. Along 25 km segments of satellite ground tracks, variability in the retrieved SSHs is between ∼2 and 3 cm (standard deviation) in the Arctic and is slightly higher (∼3 cm) in the summer and the Southern Ocean. Average sea surface tilts (along these 25 km segments) are 0.01 ± 3.8 cm/10 km in the Arctic, and slightly lower (0.01 ± 2.0 cm/10 km) in the Southern Ocean. Intra‐seasonal variability of CS‐2 dynamic ocean topography (DOT) in the ice‐covered Arctic is nearly twice as high as that of the Southern Ocean. In the Arctic, we find a correlation of 0.92 between 3 years of DOT and dynamic heights (DH) from hydrographic stations. Further, correlation of 4 years of area‐averaged CS‐2 DOT near the North Pole with time‐variable ocean‐bottom pressure from a pressure gauge and from GRACE, yields coefficients of 0.83 and 0.77, with corresponding differences of <3 cm (RMS). These comparisons contrast the length scale of baroclinic and barotropic features and reveal the smaller amplitude barotropic signals in the Arctic Ocean. Broadly, the mean DOT from CS‐2 for both poles compares well with those from the ICESat campaigns and the DOT2008A and DTU13MDT fields. Short length scale topographic variations, due to oceanographic signals and geoid residuals, are especially prominent in the Arctic Basin but less so in the Southern Ocean.

Two-Station Single Track Scheduling Problem

Single track segments are common in various railway networks, in particular in various supply chains. For such a segment, connecting two stations, the trains form two groups, depending on what station is the initial station for the journey between these two stations. Within a group the trains differ by their cost functions. It is assumed that the single track is sufficiently long so several trains can travel in the same direction simultaneously. The paper presents polynomial-time algorithms for different versions of this two-station train scheduling problem with a single railway track. The considered models differ from each other by their objective functions.

Risk Analysis of Transporting Crude Oil by Rail: Methodology and Decision Support System

In 2014, there were around 500,000 carloads of petroleum crude oil on the U.S. railroad network, an 80-fold increase since 2005. A spate of crude oil release incidents has attracted national attention to railroad transportation safety. A practical probabilistic risk analysis model to estimate the in-transit risk of transporting crude oil by rail in unit trains on main lines is described. The goal of the research for the model was to provide methods and tools for optimal safety risk management of rail transport of crude oil and other hazardous materials. The model accounts for track segment specific characteristics, including segment length, FRA track class, method of operation, and annual traffic density; train-specific characteristics such as train length, train speed, and tank car safety design; and population density along each segment. The risk model estimates segment-specific risk that is measured by the expected number of affected persons. Also, the model estimates the average interval between release incidents. The model is implemented into a decision support tool that automates risk calculation, interpretation, and visualization. The methodology and implementation tool developed can be adapted to specific train configurations on any given railroad network.

Studies of the possibility to use Gas Pixel Detector as a fast trigger tracking device

Gas Pixel Detector (GPD) technology offers new possibilities, which make them very attractive for application in existing and future accelerator experiments and beyond. GPDs combine advantages of silicon and gaseous detectors. They can be produced radiation hard and with low power consumption using relatively cheap technology. Low capacitance of the individual pixel channel allows us to obtain a large signal to noise ratio. Using a time projection method for GPD readout one obtains 3D track image with precise coordinate (31 µm) and angular information (0.40°). This feature would allow us to achieve performance of one GPD layer equal to a few layers of silicon detectors. Implementation of a fast readout and data processing at the front-end level allows one to reconstruct a track segment in less than 1 μs, and to use this information for the first level trigger generation. The relevant algorithms of data acquisition and analysis are described and the results of simulations are presented in this paper.

Clustering techniques for neuroimaging applications

Clustering has been proven useful for knowledge discovery from massive data in many applications ranging from market segmentation to bioinformatics. In this study, we focus on clustering large amounts of medical image data of the human brain to identify structures of interest. Advanced Magnetic Resonance Imaging techniques enable unprecedented insights into the complex processes in the brain. However, especially for clinical studies, a huge amount of data has to be processed in order to find patterns characterizing the structure and function of the healthy brain and its alternations associated with diseases. We survey clustering methods specifically designed for neuroimaging applications such as segmentation of fiber tracks and lesions, as well as methods that can deal with multimodal imaging data. Furthermore, we will illustrate how clustering enables knowledge discovery from data by enhancing the performance of supervised techniques and discovering meaningful subgroups of subjects. The main purpose of this study is to give an introduction on how versatile clustering techniques can be applied in neuroimaging to tackle different applications where automated methods are desired. WIREs Data Mining Knowl Discov 2016, 6:22–36. doi: 10.1002/widm.1174This article is categorized under: Algorithmic Development > Biological Data Mining Application Areas > Health Care Technologies > Structure Discovery and Clustering