Acoustic Roughness Measurement of Railhead Surface Using an Optimal Sensor Batch Algorithm

Wootae Jeong; Dahae Jeong

doi:10.3390/app10062110

Acoustic Roughness Measurement of Railhead Surface Using an Optimal Sensor Batch Algorithm

Applied Sciences ◽

10.3390/app10062110 ◽

2020 ◽

Vol 10 (6) ◽

pp. 2110 ◽

Cited By ~ 1

Author(s):

Wootae Jeong ◽

Dahae Jeong

Keyword(s):

Surface Roughness ◽

Displacement Sensors ◽

Measure Surface Roughness ◽

High Measurement ◽

Train Operation ◽

Measurement Algorithm ◽

Rolling Noise ◽

Conventional Systems ◽

Measurement Deviation ◽

Mobile Measurement

Contact and friction between wheel and rail during train operation is the main cause of the rolling noise for which railways are known. Therefore, it is necessary to accurately measure the surface roughness of wheels and rails to monitor railway noise and predict noise around tracks. Conventional systems developed to measure surface roughness have large deviations in measured values or low repeatability. The recently developed automatic mobile measurement platform known as Auto Rail Checker (ARCer) uses three displacement sensors to reduce measurement deviation and increase the accuracy of existing systems. This paper proposes enhancing the chord offset synchronization algorithm applied to the existing ARCer for high measurement precision with only two displacement sensors. As a result, when the two sensor-based measurement algorithm was applied, the spectrum level at λ = 0.314 m, the wavelength amplification associated with wheel diameter, was reduced to at least 6 dB in comparison with that of the three sensors based algorithm. We also verified the accuracy of the proposed batch algorithm through a field test on an operating rail track with a corrugated rail surface.

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Measuring Acoustic Roughness of a Longitudinal Railhead Profile Using a Multi-Sensor Integration Technique

Sensors ◽

10.3390/s19071610 ◽

2019 ◽

Vol 19 (7) ◽

pp. 1610 ◽

Cited By ~ 1

Author(s):

Dahae Jeong ◽

Han Choi ◽

Yong Choi ◽

Wootae Jeong

Keyword(s):

Field Tests ◽

Transport Systems ◽

Railway Transport ◽

Measurement Systems ◽

Structural Problems ◽

Displacement Sensors ◽

Single Sensor ◽

Rolling Noise ◽

Measurement Deviation ◽

Mobile Measurement

It is necessary to measure accurately the rolling noise generated by the friction between wheels and rails in railway transport systems. Although many systems have recently been developed to measure the surface roughness of wheels and rails, there exist large deviations in measurements between each system whose measuring mechanism is based on a single sensor. To correct the structural problems in existing systems, we developed an automatic mobile measurement platform, named the Automatic Rail Checker (ARCer), which measures the acoustic roughness of a longitudinal railhead profile maintaining a constant speed. In addition, a new chord offset synchronization algorithm has been developed. This uses three displacement sensors to improve the measuring accuracy of the acoustic roughness of a longitudinal railhead profile, thereby minimizing the limitations of mobile platform measurement systems and measurement deviation. We then verified the accuracy of the measurement system and the algorithm through field tests on rails with different surface wear conditions.

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Electrical Characterization of Low-Profile Copper Foil for Reduced Surface Roughness Loss

International Symposium on Microelectronics ◽

10.4071/isom-2016-wp52 ◽

2016 ◽

Vol 2016 (1) ◽

pp. 000358-000363 ◽

Cited By ~ 1

Author(s):

Qianfei Su ◽

A. Ege Engin ◽

Jerry Aguirre

Keyword(s):

Surface Roughness ◽

Cross Sections ◽

Transmission Lines ◽

High Frequency ◽

Printed Circuit Board ◽

Electrical Characterization ◽

Cavity Resonator ◽

Circuit Board ◽

Low Profile ◽

Measure Surface Roughness

Abstract Signal attenuation in transmission lines is a major issue for reliable transmission in high frequency range. Knowledge of the electrical parameters of printed circuit board (PCB), including dielectric constant and loss tangent, is critical. Moreover, surface roughness has a great effect on loss in high frequency. This paper demonstrates an effective simulation fitting method for electrical material characterization. Cavity resonator is chosen as the circuit for characterization. A methodology is presented to measure surface roughness from cross sections, and compared with values extracted from resonator measurements. Several materials and copper foils treatments, including low-profile, are analyzed in this paper.

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Prediction of Rolling Noise Based on Machine Learning Technique Using Rail Surface Roughness Data

Journal of the Korean society for railway ◽

10.7782/jksr.2019.22.3.209 ◽

2019 ◽

Vol 22 (3) ◽

pp. 209-217

Author(s):

Dahae Jeong ◽

Wootae Jeong

Keyword(s):

Machine Learning ◽

Surface Roughness ◽

Machine Learning Technique ◽

Learning Technique ◽

Rolling Noise

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EFFECTS OF SOME MACHINING VARIABLES IN LATHE FACING USING A PROFILOMETER TO MEASURE SURFACE ROUGHNESS

Quality Engineering ◽

10.1080/08982119208918966 ◽

1992 ◽

Vol 5 (2) ◽

pp. 243-253 ◽

Cited By ~ 4

Author(s):

NOURREDINE BOUBEKRI ◽

SHIHAB ASFOUR ◽

MORRIS H. SCHNEIDER

Keyword(s):

Surface Roughness ◽

Measure Surface Roughness

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Polymer-Based Capacity Micromachined Ultrasonic Transducer for Surface Roughness Measurement

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.661.22 ◽

2015 ◽

Vol 661 ◽

pp. 22-28 ◽

Cited By ~ 3

Author(s):

Gia Thinh Bui ◽

Yi Ze Chen ◽

Da-Chen Pang

Keyword(s):

Surface Roughness ◽

Ultrasonic Transducer ◽

Roughness Measurement ◽

Surface Roughness Measurement ◽

Measure Surface Roughness ◽

Capacitive Micromachined Ultrasonic Transducer ◽

Signal Output ◽

Good Signal ◽

Reception Mode ◽

Maximum Signal

A polymer-based capacitive micromachined ultrasonic transducer (CMUT) is developed to measure surface roughness. The transducer is designed with two groups in a ratio of two to one. By using air-coupled ultrasound, the transducer can evaluate surface roughness in five modes: full transmission/ full reception, majority transmission/ majority reception, majority transmission/ minority reception, minority transmission/ majority reception, and minority transmission/ minority reception. Experimentation shows the CMUT can identify the surface roughness using a sample of sandpaper with surface roughness Rrms ranging from 11.4μm to 179.8μm. The results indicate that the full transmission/ full reception mode has maximum signal output and the minority transmission/ majority reception mode can obtain a good signal output with a better energy efficiency rating.

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ON THE RELATIONSHIP BETWEEN WHEEL AND RAIL SURFACE ROUGHNESS AND ROLLING NOISE

Journal of Sound and Vibration ◽

10.1006/jsvi.1996.0254 ◽

1996 ◽

Vol 193 (1) ◽

pp. 149-160 ◽

Cited By ~ 41

Author(s):

D.J. Thompson

Keyword(s):

Surface Roughness ◽

Rolling Noise ◽

The Relationship

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Analysis of chip geometry and surface roughness at low speed turning in various commercial steels

MATEC Web of Conferences ◽

10.1051/matecconf/201815902018 ◽

2018 ◽

Vol 159 ◽

pp. 02018 ◽

Cited By ~ 1

Author(s):

Mudjijanto ◽

Sulistyo ◽

Rusnaldy

Keyword(s):

Surface Roughness ◽

Rapid Development ◽

Tool Material ◽

Shear Angle ◽

Test Material ◽

Low Speed ◽

Measure Surface Roughness ◽

Material Hardness ◽

Small Industries

Rapid development of technology in manufacturing facilitates the industry to produce mass, high quality and affordable products. The challenge for small industries in manufacturing is to compete for product quality. Small manufacturing industries in controlling the quality of product deal with financial problems. Chip and surface roughness of low speed machining were tested to control the quality of material mechanical properties. The purpose of this study is to investigate the relation between chip characteristic and surface roughness with material hardness. This study used a conventional lathe with low rotation, cutting depth of 1 mm, dry turning process with variations of feed rate of 0.1 mm/rev, 0.2 mm/rev and 0.3 mm/rev, test material of AISI steel (1020, 1045, 1090, D2 and 4340) and tool material from carbides. Stereoscopic Optical Microscopy (SOM) was used to measure temporary shear angle while surface roughness tester was used to measure surface roughness. The results show that the shear angle of the chip and the surface roughness correlated with the hardness of the material.

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Surface Roughness of Nanohybrid Composites with Different Monomers after Finishing and Polishing with Different Polishing Systems

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.835.41 ◽

2020 ◽

Vol 835 ◽

pp. 41-49

Author(s):

Youssef Alaa Soliman ◽

ELsayed Moustafa Mahmoud ◽

Mohammed A. Gepreel ◽

Rania Reda Afifi

Keyword(s):

Surface Roughness ◽

Bisphenol A ◽

Resin Composite ◽

Pairwise Comparison ◽

Composite Resins ◽

Dimer Acid ◽

Atomic Force ◽

Measure Surface Roughness ◽

Significant Difference ◽

Free Monomer

Background: The most frequently used monomer in commercial composite resins is bisphenol A glycidyl dimethacrylate. Bisphenol A glycidyl dimethacrylate free monomer and the long chain dimer acid based monomer were considered as an alternative method to improve mechanical and physical properties of composite resins. Objective: To study the surface roughness of different nanohybrid composites with different monomer compositions after finishing and polishing with different polishing systems. Materials and Methods: 72 composite disk specimens were prepared and divided into 3 groups (n=24) according to the resin composite that were used (harmonizekerr, venus diamondheraeuskulzer and n'duranceseptodont). Each group was subdivided into 4 subgroups (n=6) according to the polishing technique that was used (Jiffy natural universal wheelsultradent, sof-lex spiral wheels 3m espe, hilusterkerr or enhance system dentsply). Atomic force microscope was used to measure surface roughness. Results: There was statistical significant difference in surface roughness measuring among different n'durance, venus diamond and harmonize groups (Kruskal Wallis Test p<0.05). Post hock pairwise comparison revealed that venus diamond showed statistically significant higher surface roughness when compared with either n'durance and harmonize. Among the polishing systems, jiffy natural universal wheels produce the least surface roughness. Conclusion: Different monomer compositions may have direct effect on the final surface polish of the restorative materials. Clinical significance: The use of jiffy natural universal wheels may be found to result in the smoothest surface finish with the least clinical steps.

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