Abstract
As the aging of steel pipes used for sign pole is caused by the corrosion near ground, a quantitative evaluation of the corrosion location and thinning rate from the ground surface is required. Therefore, we have proposed a magnetic nondestructive testing for the steel pipes using two magnetic sensors, and it was possible to inspect the underground corrosion defects. However, in order to improve the accuracy of estimating the thinning rate and position of underground corrosion, the optimization of the inclination angle of the magnetic sensor probe and the distance between two magnetic sensors has been required. Therefore, in order to extract the signal change caused by the thinning rate of the test sample and the measurement distance, the distance dependence which is the relationship between the signal intensity and the measurement distance was measured and the measured value was normalized by the signal intensity measured at uncorroded area. As a result, the difference between the signal intensity at the uncorroded part and that near the corrosion defect could be clearly extracted. Furthermore, the rate of change of signal intensity increased by changing the tilt angle of probe and the distance between two sensors. Using the optimized magnetic sensor probe and applying the normalized distance dependence, we succeeded in the quantitative evaluation of the thinning rate and position of corrosion defects.
Original language | English |
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Publication status | Published - 2019 |
Event | 10th International Workshop NDT in Progress 2019 - Prague, Czech Republic Duration: Oct 7 2019 → Oct 9 2019 |
Conference
Conference | 10th International Workshop NDT in Progress 2019 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 10/7/19 → 10/9/19 |
Keywords
- Corrosion near the ground
- ELECT
- Magnetic spectrum curve
- Nondestructive testing
ASJC Scopus subject areas
- Modelling and Simulation
- Mechanics of Materials
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Computer Science Applications
- Safety, Risk, Reliability and Quality