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

2018 ◽  
Vol 233 (3) ◽  
pp. 337-355 ◽  
Author(s):  
Jiaqi Ye ◽  
Edward Stewart ◽  
Clive Roberts
Keyword(s):  
3D Reconstruction ◽  
3D Model ◽  
Surface Defects ◽  
Railway Track ◽  
Sensor Technology ◽  
Prototype System ◽  
Laser Sensor ◽  
Railway Systems ◽  
3D Data Processing ◽  
Inspection Techniques

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.

A robot hand-eye calibration method of line laser sensor based on 3D reconstruction

2021 ◽  
Vol 71 ◽  
pp. 102136
Author(s):  
Mingyang Li ◽  
Zhijiang Du ◽  
Xiaoxing Ma ◽  
Wei Dong ◽  
Yongzhuo Gao
Keyword(s):  
3D Reconstruction ◽  
Calibration Method ◽  
Laser Sensor ◽  
Robot Hand

Assessing the Condition and Estimating the Remaining Lives of Pressure Components in a Methanol Plant Reformer: Part 1 — NDE

2016 ◽  
Author(s):  
Brian E. Shannon ◽  
Carl E. Jaske ◽  
Gustavo Miranda
Keyword(s):  
High Temperature ◽  
Creep Damage ◽  
Sensor Technology ◽  
Special Focus ◽  
Laser Measurements ◽  
Typical Data ◽  
Multiple Sensor ◽  
High Temperature Components ◽  
Inspection Techniques ◽  
Non Destructive

Statoil Tjelbergodden operates a 2,400 ton/day methanol plant in Norway. In order to assess the condition and reliability of high temperature components within the reformer, a series of advanced non-destructive examination (NDE) technologies were applied to radiant catalyst tubes, outlet pigtails, and outlet collection headers. The inspection techniques were selected and developed to provide data that could easily be used in the engineering assessment of the high-temperature components. Special focus was given to detecting and quantifying high-temperature creep damage. This paper describes the NDE techniques that were employed and provides examples of typical data obtained by using the techniques. Catalyst tubes were inspected using the H SCAN® (Figure 1) multiple sensor technology. This technique utilizes two types of ultrasonic sensors, eddy current sensors, laser measurements, and elevation location sensors in scanning each catalyst tube. The H SCAN® P-CAT™ (Figure 2) technique is applied to outlet pigtails, while the H SCAN® H-CAT™ (Figure 3) technique is applied to outlet headers.

scholarly journals Purwarupa Alat Kalibrasi Kerataan Bidang Kerja menggunakan Laser Sensor

2018 ◽  
Vol 6 (2) ◽  
pp. 274
Author(s):  
BUDI SUGANDI ◽  
SURADI WIYONO
Keyword(s):  
Prototype System ◽  
Laser Sensor ◽  
Important Process ◽  
Manual Measurement ◽  
Industrial Manufacturing ◽  
Die Attach ◽  
Pick And Place ◽  
Component Assembly ◽  
Keywords Laser

ABSTRAKSalah satu elemen teknologi pendukung dari industri manufaktur elektronika adalah mesin Die Attach. Mesin ini digunakan pada proses assembly komponen dengan metode pick and place komponen pada material. Sebagai proses yang penting dalam industri manufaktur, mesin ini memerlukan kalibrasi secara reguler dan tepat yang akan menjadi kunci sukses dari kualitas suatu produksi. Penelitian ini bertujuan membuat suatu purwarupa alat yang digunakan sebagai pengontrol kalibrasi dengan menggunakan laser sensor. Proses kalibrasi dilakukan dengan cara mengukur kerataan titip sisi work holder menggunakan laser sensor. Kerataan didapatkan dengan membandingkan jarak yang terukur oleh laser sensor pada tiap titik uji. Jarak yang sama pada tiap titik uji menunjukkan kerataan dari work holder. Pergerakan laser sensor dikontrol oleh dua buah motor yang bergerak ke arah sumbu X dan Y. Alat ini telah diuji dengan mengkalibrasi pada empat sisi work holder. Hasil pengujian kemudian dibandingkan dengan pengukuran manual dan didapatkan error rata-rata pengukuran sekitar 4%.Kata kunci: Laser sensor, kerataan, kalibrasi, die attach machine ABSTRACTOne of the element technology supporting an industrial manufacturing is Die Attach machine. This machine is used at component assembly using component pick and place. As an important process, this machine requires regular and precise calibration to support quality of the product. This research aims to build a prototype system using laser sensor which can be used as calibration instrument. The callibration proses was done by measuring the flatness of each side of work holder using laser sensor. The flatness was obtained by comparing the distance of each testing point. The same distance on each testing point represented the flatness of the wrok holder. The movement of laser sensor was controlled by two motors which moved to X and Y axis. The system has been tested to calibrate each side of work holder. The experimental results were then compare with manual measurement and showed the measurement error about 4%.Keywords: Laser sensor, flatness, callibration, die attach machine.

3D Metallic Surface Acquisition for Inspection and Reading Character

2013 ◽  
Vol 811 ◽  
pp. 394-400
Author(s):  
T. Suesut ◽  
S. Gulphanich ◽  
K. Roonprasang
Keyword(s):  
Laser Scanning ◽  
Surface Defects ◽  
Low Cost ◽  
Least Square ◽  
Metallic Surface ◽  
Prototype System ◽  
Production Environment ◽  
Smooth Approximation ◽  
Numerical Effort ◽  
Discrete Orthogonal

This paper presents a real-time implementation of 3D acquisition for reading text and inspection the metallic surface based on light sectioning. A measurement is achieved with a standard low cost CMOS camera. Surface defects are modeled as deviations in the local relief from a smooth approximation of the surface. Discrete orthogonal bases are used to generate a smoothed global model of the surface structure. Modified discrete Tchebychev polynomials are used as orthogonal basis functions to perform least square approximations of the geometry. QR decomposition is used to obtain a unitary basis, minimizing the numerical effort when modeling surfaces. The result of test measurements on copper sheets in a production environment is presented to demonstrate the surface inspection. Another result is shown the readable character on the textured metallic surface after the proposed processing. A prototype system of the laser scanning instrument can be implemented in a production line as well.

scholarly journals Software Design of a Railway Signal Monitoring System based on Optical Fiber Sensing

2018 ◽  
Vol 14 (08) ◽  
pp. 134
Author(s):  
Ma Chun-ying ◽  
Li Biqing
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Data Storage ◽  
Online Monitoring ◽  
Railway Track ◽  
Time Data ◽  
Railway Systems ◽  
Management Platform ◽  
Railway Signal ◽  
Optical Fiber Sensing

The current railway track circuit monitoring system is prone to disturbances that can result in accidents. Meanwhile, basic signaling equipment is slow and cannot achieve satisfactory real-time data acquisition speed. This study aims to solve the aforementioned problems by designing an online monitoring and management platform for railway signal infrastructure, which is based on the graphical programming language LabVIEW. Online monitoring and management of railways’ basic signaling equipment allow real-time collection and communication of various signal equipment data. These processes also enable signal processing, chart display, acousto-optic alarm, user authority management, data storage, data query analysis, and report printing. The test results show that the LabVIEW-based basic signaling equipment for monitoring and managing railway systems can transmit data correctly and steadily, thereby resulting in convenient and ideal operation.

scholarly journals Laser Sensors for Displacement, Distance and Position

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1924 ◽  
Author(s):  
Young Soo Suh
Keyword(s):  
Manufacturing Industry ◽  
Time Of Flight ◽  
Autonomous Driving ◽  
Sensor Technology ◽  
Laser Sensor ◽  
Laser Sensors ◽  
Interferometric Sensors ◽  
Industry Applications ◽  
Surface Profiles ◽  
Traditional Manufacturing

Laser sensors can be used to measure distances to objects and their related parameters (displacements, position, surface profiles and velocities). Laser sensors are based on many different optical techniques, such as triangulation, time-of-flight, confocal and interferometric sensors. As laser sensor technology has improved, the size and cost of sensors have decreased, which has led to the widespread use of laser sensors in many areas. In addition to traditional manufacturing industry applications, laser sensors are increasingly used in robotics, surveillance, autonomous driving and biomedical areas. This paper outlines some of the recent efforts made towards laser sensors for displacement, distance and position.

scholarly journals Controlling the Flight of a Drone and Its Camera for 3D Reconstruction of Large Objects

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2333 ◽  
Author(s):  
Simone Mentasti ◽  
Federico Pedersini
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
3D Model ◽  
Image Sequence ◽  
Scene Reconstruction ◽  
Entire Process ◽  
Reconstruction Software ◽  
Different Shapes ◽  
User Intervention

In this paper we present a simple stand-alone system performing the autonomous acquisition of multiple pictures all around large objects, i.e., objects that are too big to be photographed from any side just with a camera held by hand. In this approach, a camera carried by a drone (an off-the-shelf quadcopter) is employed to carry out the acquisition of an image sequence representing a valid dataset for the 3D reconstruction of the captured scene. Both the drone flight and the choice of the viewpoints for shooting a picture are automatically controlled by the developed application, which runs on a tablet wirelessly connected to the drone, and controls the entire process in real time. The system and the acquisition workflow have been conceived with the aim to keep the user intervention minimal and as simple as possible, requiring no particular skill to the user. The system has been experimentally tested on several subjects of different shapes and sizes, showing the ability to follow the requested trajectory with good robustness against any flight perturbations. The collected images are provided to a scene reconstruction software, which generates a 3D model of the acquired subject. The quality of the obtained reconstructions, in terms of accuracy and richness of details, have proved the reliability and efficacy of the proposed system.

Nature 4.0 – Intelligent networked systems for ecosystem monitoring

2020 ◽  
Author(s):  
Nicolas Friess ◽  
Marvin Ludwig ◽  
Christoph Reudenbach ◽  
Thomas Nauss ◽  
Keyword(s):  
Remote Sensing ◽  
Networked Systems ◽  
Third Party ◽  
Mesh Network ◽  
Sensor Technology ◽  
Conservation Strategies ◽  
Prototype System ◽  
Ecosystem Monitoring ◽  
Spatial Coverage ◽  
Environmental Monitoring System

<p>Successful conservation strategies and adaptive management require frequent observations and assessments of ecosystems. Depending on the conservation target this is commonly achieved by monitoring schemes carried out locally by experts. In general, these expert surveys provide a high level of detail which however is traded-off against the limited spatial coverage and repetition with which they are commonly executed. Thus, it is common practice to spatially expand these observations by remote sensing techniques. For a resilient monitoring both the expert observations and the spatio-temporal upscaling have to be extended by automated measurements and reproducible modelling.  Therefore, Nature 4.0 is developing a prototype of a modular environmental monitoring system for spatially and temporally high-resolution observations of species, habitats and key processes.  This prototype system is being developed in the Marburg Open Forest, an open research, education and development platform for environmental observation methods. Here, we present the experiences and challenges of the first year with a focus on the conceptual design and the first implementation of the core observation subsystems and their comparison with the data collected by classical field surveys and remote sensing. The spatially distributed acquisition of abiotic and biotic environmental parameters is based on self-developed as well as third party sensor technology.  This includes an automated area-wide radiotracking system of bats and birds and sensor units for measurements of microclimatic conditions and tree sap flow as well as spectral imaging and soundscape recording. The backbone of the automated data collection and transmission is an autonomous LoRa and WiFi mesh network, which is connected to the internet via radio relay. By utilizing powerful data integration and analysis methods, the system will enable researchers, conservationists and the public to effectively observe landscapes through a set of diverse lenses. Here, we present first results as well as an outlook for future developments of intelligent networked systems for ecosystem monitoring.</p>

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