全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Application of t-Test Statistical Analysis to Assess the Need for Calibration Verification in NDT Ultrasonic Thickness Measurements under Varying Environmental Conditions

DOI: 10.4236/mme.2026.162002, PP. 19-32

Keywords: Ultrasonic Thickness Measurement, Non-Destructive Testing (NDT), Ultrasonic Testing (UT), Independent Samples t-Test, Statistical Analysis, Calibration Procedures, Environmental Effects, Pipeline Inspection, Box Plot Distribution, Normal Quantile Plot

Full-Text   Cite this paper   Add to My Lib

Abstract:

Ultrasonic thickness measurement is widely used in non-destructive testing (NDT) to monitor pipeline integrity and detect wall thinning or corrosion without damaging the component. However, measurement accuracy can be influenced by environmental conditions such as temperature variations, couplant condition, and operational shifts. This study investigates the effect of environmental conditions associated with day and night operational shifts on ultrasonic thickness measurements using statistical analysis. A total of 120 ultrasonic thickness readings were analyzed over three consecutive days. For each day, two independent groups were collected, consisting of 20 measurements during the day shift and 20 measurements during the night shift. The mean thickness values recorded during the day shifts were approximately 10.003 mm, 10.001 mm, and 10.000 mm for Days 1, 2, and 3 respectively, while the night shift measurements produced higher mean values of approximately 10.089 mm, 10.095 mm, and 10.096 mm. To determine whether these differences were statistically significant, an Independent Samples t-test was applied at a significance level of α = 0.05. The calculated t-ratios were 10.056, 12.867, and 12.724 for Days 1, 2, and 3 respectively, with corresponding p-values less than 0.0001. The combined dataset showed a mean difference of approximately 0.092 mm with a 95% confidence interval ranging from 0.083 mm to 0.101 mm. Graphical analyses using box plot distributions and normal quantile plots further supported the statistical findings. The results indicate that environmental conditions associated with operational shifts may influence ultrasonic thickness measurements. Therefore, periodic calibration verification during different operational shifts may help improve measurement reliability in industrial inspection applications.

References

[1]  Abbasi, K. and Alobaidi, W.M. (2018) Estimation of Time-of-Flight Based on Threshold and Peak Analysis Method for Microwaves Signals Reflected from the Crack. Nondestructive Testing and Evaluation, 33, 393-404.
https://doi.org/10.1080/10589759.2018.1495204
[2]  Alobaidi, W.M., Alkuam, E.A. and Sandgren, E. (2018) Development of an Optimized Neural Network for the Detection of Pipe Defects Using a Microwave Signal. Journal of Pressure Vessel Technology, 140, Article ID: 041501.
https://doi.org/10.1115/1.4040360
[3]  Alobaidi, W.M., Kintner, C.E., Alkuam, E.A., Sasaki, K., Yusa, N., Hashizume, H., et al. (2017) Experimental Evaluation of Novel Hybrid Microwave/Ultrasonic Technique to Locate and Characterize Pipe Wall Thinning. Journal of Pressure Vessel Technology, 140, Article ID: 011501.
https://doi.org/10.1115/1.4038517
[4]  Alobaidi, W.M. and Sandgren, E. (2016) Classification of the Extent of Wall Thinning in Pipes Based on Simulations in the Time and Frequency Domain. ASME 2016 Pressure Vessels and Piping Conference, Vancouver, 17-21 July 2016.
https://doi.org/10.1115/pvp2016-63387
[5]  Alobaidi, W.M. and Sandgren, E. (2016) High-Efficiency Remote Measurement of Pipe Defect Using RF/UT Technologies: A Theoretical Analysis Part One—Straight Beam UT. ASME 2016 Pressure Vessels and Piping Conference, Vancouver, 17-21 July 2016.
https://doi.org/10.1115/pvp2016-63624
[6]  Alobaidi, W.M. and Sandgren, E. (2016) Detection of Defects in Spiral/Helical Pipes Using RF Technology. Proceedings of the 11th Pipeline Technology Conference, Berlin, 23-25 May 2016, 22-33.
[7]  Alobaidi, W.M., Alkuam, E.A., Sandgren, E. and Al-Rizzo, H.M. (2015) Enhancing Production Efficiency of Oil and Natural Gas Pipes Using Microwave Technology. Energy and Power Engineering, 7, 440-450.
https://doi.org/10.4236/epe.2015.710043
[8]  Alobaidi, W.M., Alkuam, E.A., Al-Rizzo, H.M. and Sandgren, E. (2015) Applications of Ultrasonic Techniques in Oil and Gas Pipeline Industries: A Review. American Journal of Operations Research, 5, 274-287.
https://doi.org/10.4236/ajor.2015.54021
[9]  Alobaidi, W., Sandgren, E. and Al-Rizzo, H. (2015) A Survey on Benchmark Defects Encountered in the Oil Pipe Industries. International Journal of Scientific & Engineering Research, 6, 844-851.
[10]  Alobaidi, W.M. (2017) Application of Microwave and Ultrasonic Techniques for Defect Detection in Pipes. Ph.D. Thesis, University of Arkansas.
[11]  Niu, L. and Cheng, Y.F. (2008) Development of Innovative Coating Technology for Pipeline Operation Crossing the Permafrost Terrain. Construction and Building Materials, 22, 417-422.
https://doi.org/10.1016/j.conbuildmat.2007.06.001
[12]  Perez, M., Kehr, J.A., Attaguiles, S. and Smith, M. (2008) New Technology Helps Develop Coatings for High-Operating Temperature Pipelines. CORROSION 2008 Conference, New Orleans, 16-20 March 2008, NACE-08040.
[13]  Montgomery, D.C. (2019) Design and Analysis of Experiments. 10th Edition, Wiley.
[14]  Guo, X. (2003) A Statistical Study on the Relationship between Tensile Strength and Ultrasonic Velocity of Cast Iron. International Journal of Cast Metals Research, 16, 221-225.
https://doi.org/10.1080/13640461.2003.11819586
[15]  Gupta, S., Singh, D.S. and Ray, A. (2008) Statistical Pattern Analysis of Ultrasonic Signals for Fatigue Damage Detection in Mechanical Structures. NDT & E International, 41, 491-500.
https://doi.org/10.1016/j.ndteint.2008.06.001
[16]  Lizzi, F.L., Feleppa, E.J., Astor, M. and Kalisz, A. (1997) Statistics of Ultrasonic Spectral Parameters for Prostate and Liver Examinations. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 44, 935-942.
https://doi.org/10.1109/58.655209
[17]  Balle, F. and Eifler, D. (2012) Statistical Test Planning for Ultrasonic Welding of Dissimilar Materials Using the Example of Aluminum-Carbon Fiber Reinforced Polymers (CFRP) Joints. Materialwissenschaft und Werkstofftechnik, 43, 286-292.
https://doi.org/10.1002/mawe.201200943
[18]  Kumar, C.N.A., Krishnaraj, R., Sakthivel, M. and Arularasu, M. (2013) Implementation of Safety Education Program for Material Handling Equipment in Construction Sites and Its Effectiveness Analysis Using T-Test. International Journal of Applied Environmental Sciences, 8, 1961-1969.
[19]  Afifah, S., Mudzakir, A. and Nandiyanto, A.B.D. (2022) How to Calculate Paired Sample T-Test Using SPSS Software: From Step-By-Step Processing for Users to the Practical Examples in the Analysis of the Effect of Application Anti-Fire Bamboo Teaching Materials on Student Learning Outcomes. Indonesian Journal of Teaching in Science, 2, 81-92.
https://doi.org/10.17509/ijotis.v2i1.45895
[20]  Kulkarni, N.S. and Deore, E.R. (2014) Experimental and T-Test (Testing Hypothesis) Approach in Vibration Reduction. International Journal of Mechanical Engineering and Robotics Research, 3, 611-618.
[21]  JMP Statistical Discovery LLC. (2026) JMP® 19. Cary, NC.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133