Application of LIDAR technology for rail surface monitoring and quality indexing

2017 ◽  
Vol 232 (5) ◽  
pp. 1398-1406 ◽  
Author(s):  
Masood Taheri Andani ◽  
Abdullah Mohammed ◽  
Ashish Jain ◽  
Mehdi Ahmadian
Keyword(s):  
Doppler Frequency ◽  
Light Detection And Ranging ◽  
Doppler Lidar ◽  
Frequency Range ◽  
Absorption Properties ◽  
Surface Conditions ◽  
Lidar Measurements ◽  
Rail Inspection ◽  
Surface Monitoring ◽  
Surface Figure

This paper investigates the application of Doppler Light Detection and Ranging (LIDAR) sensors for the assessment of the top of rail lubricity condition and layer material. Different top of rail conditions are distinguished by the system using a new pair of rail surface indices defined based on LIDAR measurements. These indices provide quantitative representations of the top of rail condition due to the fact that Doppler frequency range and spectral magnitude of a backscattered LIDAR beam are functions of the rail surface figure as well as the light absorption properties of the surface material. Laboratory tests are conducted to demonstrate the feasibility of the proposed top of rail indexing operation. The results indicate that LIDAR sensors are capable of detecting and distinguishing between different top of rail surface conditions. Instrumenting rail inspection vehicles with Doppler LIDAR systems reduces reliance on empirical top of rail lubricity and surface assessments (such as observing the sheen of the rail or tactilely sensing various residues on the rail), in favor of reliable and repeatable measurements.

scholarly journals Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland

2021 ◽  
Vol 13 (13) ◽  
pp. 2433
Author(s):  
Shu Yang ◽  
Fengchao Peng ◽  
Sibylle von Löwis ◽  
Guðrún Nína Petersen ◽  
David Christian Finger
Keyword(s):  
Machine Learning ◽  
Weather Conditions ◽  
Dust Storms ◽  
Machine Learning Algorithms ◽  
Lidar Data ◽  
Data Sets ◽  
Doppler Lidar ◽  
Lidar Measurements ◽  
Using Data ◽  
Filter Noise

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.

scholarly journals Acoustic Panels Made of Paper Sludge and Clay Composites

2021 ◽  
Vol 13 (2) ◽  
pp. 637
Author(s):  
Tomas Astrauskas ◽  
Tomas Januševičius ◽  
Raimondas Grubliauskas
Keyword(s):  
Absorption Coefficient ◽  
Sound Absorption ◽  
Composite Panel ◽  
Sound Absorption Coefficient ◽  
Core Material ◽  
Paper Sludge ◽  
Frequency Range ◽  
Absorption Properties ◽  
Air Gaps ◽  
The Core

Studies on recycled materials emerged during recent years. This paper investigates samples’ sound absorption properties for panels fabricated of a mixture of paper sludge (PS) and clay mixture. PS was the core material. The sound absorption was measured. We also consider the influence of an air gap between panels and rigid backing. Different air gaps (50, 100, 150, 200 mm) simulate existing acoustic panel systems. Finally, the PS and clay composite panel sound absorption coefficients are compared to those for a typical commercial absorptive ceiling panel. The average sound absorption coefficient of PS-clay composite panels (αavg. in the frequency range from 250 to 1600 Hz) was up to 0.55. The resulting average sound absorption coefficient of panels made of recycled (but unfinished) materials is even somewhat higher than for the finished commercial (finished) acoustic panel (αavg. = 0.51).

Dual-Doppler Lidar Measurements for Improving Dispersion Models

2005 ◽  
Vol 86 (6) ◽  
pp. 825-838 ◽  
Author(s):  
Chris G. Collier ◽  
Fay Davies ◽  
Karen E. Bozier ◽  
Anthony R. Holt ◽  
Doug R. Middleton ◽  
...  
Keyword(s):  
Doppler Lidar ◽  
Dispersion Models ◽  
Lidar Measurements

Railway track irregularity and curvature estimation using doppler LIDAR fiber optics

2016 ◽  
Vol 232 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Masood Taheri Andani ◽  
Andrew Peterson ◽  
Josh Munoz ◽  
Mehdi Ahmadian
Keyword(s):  
Fiber Optics ◽  
Field Testing ◽  
Railway Track ◽  
Vehicle Speed ◽  
Doppler Lidar ◽  
Close Match ◽  
Track Geometry ◽  
Lidar Measurements ◽  
Curvature Estimation ◽  
Geometry Measurement

The application of Doppler-based LIght Detection and Ranging (LIDAR) technology for determining track curvature and lateral irregularities, including alignment and gage variation, are investigated. The proposed method uses track measurements by two low-elevation, slightly tilted LIDAR sensors nominally pointed at the rail gage face on each track. The Doppler LIDAR lenses are installed with a slight forward angle to measure track speed in both longitudinal and lateral directions. The lateral speed measurements are processed for assessing the track gage and alignment variations, using a method that is based on the frequency bandwidth dissimilarities between the vehicle speed and track geometry irregularity. Using the results from an extensive series of tests with a body-mounted Doppler LIDAR system on-board a track geometry measurement railcar, the study indicates a close match between the LIDAR measurements and those made with existing sensors on-board the railcar. The field testing conducted during this study indicates that LIDAR sensors could provide a reliable, non-contact track monitoring instrument for field use in various weather and track conditions, potentially in a semi-autonomous or autonomous manner.

Method of Testing of Sound Absorption Properties of Materials Intended for Ultrasonic Noise Protection

2013 ◽  
Vol 38 (2) ◽  
pp. 191-195 ◽  
Author(s):  
Dariusz Pleban
Keyword(s):  
Sound Absorption ◽  
Free Field ◽  
Tone Burst ◽  
Mineral Wool ◽  
Frequency Range ◽  
Absorption Properties ◽  
Open Cell Foam ◽  
Properties Of Materials ◽  
Cell Foam

Abstract Efficient ultrasonic noise reduction by using enclosures requires the knowledge of absorbing properties of materials in the frequency range above 4 kHz. However, standardized methods enable determination of absorption coefficients of materials in the frequency range up to 4 kHz. For this reason, it is proposed to carry out measurements of the sound absorption properties of materials in the free field by means of a tone-burst technique in the frequency range from 4 kHz to 40 kHz at angles of incidence varying from 0° to 60°. The absorption coefficient of a material is calculated from the reflection coefficient obtained by reflecting a tone-burst from both a perfectly reflecting panel and a combination of this panel and the sample of the tested material. The tests results show that mineral wool and polyurethane open-cell foam possess very good absorbing properties in this frequency range.

Magnetization and Microwave Absorption Properties of La0.67 Sr0.33 MnO3 with Different Particle Size

2011 ◽  
Vol 374-377 ◽  
pp. 1541-1544 ◽  
Author(s):  
Yu Lan Cheng ◽  
Ping Xia ◽  
Ke Xiang Wei ◽  
Quan Bai
Keyword(s):  
Particle Size ◽  
Sinter Temperature ◽  
Microwave Absorption ◽  
Reflection Loss ◽  
Sol Gel ◽  
Frequency Range ◽  
Absorption Properties ◽  
Microwave Absorption Properties ◽  
Measured Frequency Range ◽  
Maximum Reflection Loss

La 0.67 Sr 0.33 MnO 3 particles with different particle size have been prepared by sol-gel method. The structure, magnetization and microwave absorption properties have been investigated. The results show that the particle size can be controlled by sinter temperature. The peaks of the maximum reflection loss (RL) move to higher frequency regions with increasing particle size. The value of the maximum RL is -32 dB at 10.2GHz with a particle size of 58.5nm. The bandwidth with a RL exceeding -8dB reached 1.6GHz in the whole measured frequency range, suggesting that La 0.67 Sr 0.33 MnO 3 particles are promising for application as a wideband and strong absorption building microwave absorber.

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