A fiber optic sensor for the measurement of surface roughness and displacement using artificial neural networks

Zhang, K.; Butler, C.; Yang, Qing; Lu, Yicheng

doi:10.1109/19.650796

Cited by 47 publications

(20 citation statements)

References 8 publications

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“…• in [16], the parameters characterizing the surface roughness and displacement are estimated on the basis of the data from a seven-fiber optic sensor; • in [17], the cell damages caused by tumours are identified on the basis of the tissue impedance parameters.…”

Section: Examples Of Quasi-dynamic Reconstruction Problemsmentioning

confidence: 99%

On teaching measurement applications of digital signal processing

Morawski

2007

Measurement

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Section: Examples Of Quasi-dynamic Reconstruction Problemsmentioning

confidence: 99%

On teaching measurement applications of digital signal processing

Morawski

2007

Measurement

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“…With this system, nanometer and smaller displacements can be measured precisely [3,4]. Furthermore, since the measurement is performed with a laser beam, a contact free measurement can be achieved [5].…”

Section: Introductionmentioning

confidence: 99%

A Study on Performance Effects of Standard and Stabilized He-Ne Lasers in an Interferometric Measurement System

Böcekçi

2016

Acta Phys. Pol. A

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Stabilized He-Ne lasers are commonly utilized in interferometric systems, and provide easy and accurate results. The main reason for their extensive use is their output beam's strength and stability. However, these are relatively high in cost. In interferometric measurement systems, standard He-Ne lasers can also be used. This type of lasers has a lower cost, but their output beam strength can fluctuate in time. And this in turn adversely affects the measurement performance. In this study, a standard He-Ne and a stabilized He-Ne lasers were used in the same measurement system. The measurement errors caused by the fluctuation of the output beam of the standard He-Ne laser are minimized by using a video processing technique. When the obtained results were compared with the ideal values, the relative error for the system with the stabilized He-Ne laser was recorded as 0.2%, while for the system with the standard He-Ne laser a relative error rate of 0.3% was achieved. When the results are analyzed, it is evident that in measurement systems with a standard He-Ne laser, the system performance can be boosted with a video processing technique, and that its results can achieve values closer to the performance of stabilized He-Ne lasers.

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“…In fact, the surface of the object to be detected is not a mirror plate, so at the surface both the diffuse reflection and normal reflection occur at the same time. The intensity of the reflected light can be expressed as [6] …”

Section: Modeling Relationship Between the Intensity Of Reflected Ligmentioning

confidence: 99%

On-line defect detection of aluminum coating using fiber optic sensor

Patil

Shaligram

2014

Photonic Sens

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Aluminum metallization using the sprayed coating for exhaust mild steel (MS) pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as defects in the surface coating. This paper reports a novel configuration of the fiber optic sensor for on-line checking the aluminum metallization uniformity and hence for defect detection. An optimally chosen high bright 440 nm BLUE LED (light-emitting diode) launches light into a transmitting fiber inclined at the angle of 60° to the surface under inspection placed adequately. The reflected light is transported by a receiving fiber to a blue enhanced photo detector. The metallization thickness on the coated surface results in visually observable variation in the gray shades. The coated pipe is spirally inspected by a combination of linear and rotary motions. The sensor output is the signal conditioned and monitored with RISHUBH DAS. Experimental results show the good repeatability in the defect detection and coating non-uniformity measurement.

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A fiber optic sensor for the measurement of surface roughness and displacement using artificial neural networks

Abstract: Index Terms-Artificial neural network, displacement, fiber optic sensor, measurement, surface roughness.

Cited by 47 publications

References 8 publications

On teaching measurement applications of digital signal processing

On teaching measurement applications of digital signal processing

A Study on Performance Effects of Standard and Stabilized He-Ne Lasers in an Interferometric Measurement System

On-line defect detection of aluminum coating using fiber optic sensor

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