Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.

Multiple extended target tracking algorithm based on Gaussian surface matrix

In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix（GSM） into the framework of the random finite set（RFS） theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density（PHD） filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatially close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.

Transport phenomena and keyhole evolution process in laser welding of stainless steel

Knowledge of transport phenomena and keyhole evolution is important for controlling laser welding process. However, it is still not well understood by far due to the complex phenomena occurring in a wide temperature range. A transient 3D model including heat transfer, fluid flow and tracking of free surface is built in this study. The transport phenomena are investigated by calculating the temperature and velocity fields. The 3D dynamic keyhole evolution process is revealed through tracking free surface using volume-of-fluid method. The results show that the keyhole deepening speed decreases with laser welding process before the quasi-steady state is reached. The plasma can greatly affect the keyhole depth through absorbing a great amount of laser energy and thus lowering the recoil pressure. Moreover, the relationship between keyhole depth and weld penetration is also discussed. This paper can help to better understand the dynamics in molten pool and then improve laser welding process.

Surface tracking assessment and interaction in texture space

In this paper, we present a novel approach for assessing and interacting with surface tracking algorithms targeting video manipulation in postproduction. As tracking inaccuracies are unavoidable,we enable the user to provide small hints to the algorithms instead of correcting erroneous results afterwards. Based on 2D mesh warp-based optical flow estimation, we visualize results and provide tools for user feedback in a consistent reference system, texture space. In this space, accurate tracking results are reflected by static appearance, and errors can easily be spotted as apparent change. A variety of established tools can be utilized to visualize and assess the change between frames. User interaction to improve tracking results becomes more intuitive in texture space, as it can focus on a small region rather than a moving object.We show how established tools can be implemented for interaction in texture space to provide a more intuitive interface allowing more effective and accurate user feedback.

Near-ground trajectory planning for UAVs via multi-resolution hybrid voxel-surfel map

This paper is concerned with trajectory planning problems for UAVs operating near ground.Most existing studies focus on solving the problem of collision-free trajectory planning between pre-defined path points,but ignore the need of navigation method for UAVs working on specific operating surfaces in near-ground space.In this paper,a novel near-ground trajectory planning framework is proposed,where the hybrid voxel-surfel map is developed to model the environment with special attention to the uneven operating surface.To improve the frequency of updates,a probability-based surfel fusion method and a resolution adaptive adjustment method based on the fusion result are proposed in this paper.By using possibility information in the map,a path search method is established to generate the initial trajectory.The trajectory is then further optimized based on map gradient information to generate a final trajectory that tracks the specified operating surface according to the task requirements.Compared with existing methods,the multi-resolution hybrid voxel-surfel map proposed in this paper has advantages in terms of operating efficiency.A series of experiments in simulated and real scenarios validate the effectiveness of the proposed trajectory planning framework.