Magnetic flux leakage technique to detect loss in metallic area in external post-tensioning systems

Karthik, Madhu M.; Terzioglu, Tevfik; Hurlebaus, Stefan; Hueste, Mary Beth D.; Weischedel, H.R.; Stamm, Ronald

doi:10.1016/j.engstruct.2019.109765

Cited by 21 publications

(14 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The leak is detected using a magnetic field detector (made up of Hall-effect sensors) placed between the magnet's poles and is sensitive to the change in the magnetic field. The residual approach involves bringing the steel to full magnetic saturation to erase its unknown magnetic history, then removing the magnet and passing the sensors over the portion to detect the remaining magnetic field [53,54]. Figure 7 [9] shows the schematic of the sensor probe, full head sensor , half head sensor , and the connection of the NDE extension to the computer .…”

Section: Electromagnetic Methodsmentioning

confidence: 99%

Risk-Based Selection of Inspection Method for External Post-Tensioning System of Bridges

Taeby

Mehrabi

2022

Applied Sciences

View full text Add to dashboard Cite

The increasing complexity associated with the maintenance of bridges with post-tensioning tendons, along with growing public awareness to ensure higher levels of safety in bridges, has put additional pressure on the designers and the owners to find innovative solutions to ensure safe as well as economically viable solutions. Risk-based inspection and maintenance helps in finding such solutions and, thus, it is gaining more importance in the field of infrastructure management. Within the framework of current risk-based inspection methodologies, it is normally assumed that the method by which the inspection is performed is known beforehand. However, the selection of the inspection method by itself should be given importance and viewed as the first key step for any inspection. The lack of quantitative data in the initiation step makes this selection uncertain and the decision making rather subjective. Despite recent release of comprehensive reports and other publications on condition assessment of bridges with post-tensioning systems, a quantitative approach and a decision-making framework for the selection of the inspection method and associated protocol are still missing, and the inspection strategy and methods are determined purely by the experience of the inspector or the owner. In this paper, a simple and structured risk-based selection methodology is presented that can bridge the existing knowledge gap. The proposed methodology uses a statistical approach to quantify the likelihood of the inspection error utilizing a variety of applicable NDE (Non-destructive Evaluation) methods. To give the methodology both accuracy and practicality, the specifications for the national bridge inventory (SNBI) condition rating was incorporated in this methodology and the accuracy of the inspection methods are measured against determining the correct SNBI condition. Application and effectiveness of the proposed methodology are demonstrated using a case study inspection conducted earlier by the authors. The results, in this case, converged to the selection of one of the NDE methods, which consequently was accepted by the bridge stakeholders.

show abstract

Section: Electromagnetic Methodsmentioning

confidence: 99%

Risk-Based Selection of Inspection Method for External Post-Tensioning System of Bridges

Taeby

Mehrabi

2022

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Figure 6 is a schematic of J ⃗ ", KL and M ⃗ ", KL in the xz-plane by VDM at the crack tip. According to the VDM in the state in which the magnetic domain is not deformed, as shown in Figure 3c, Equation ( 13) can be expressed as Equation (18). This is generally represented by Figure 6b,c.…”

Section: Magnetic Domain Models For Stress and Fatigue Cracksmentioning

confidence: 99%

“…A study on magnetic metal memory (MMM) has been reported in leakage magnetic flux testing which is able to detect an internal defect by measuring the self-magnetic flux leakage (SMFL) [14][15][16][17]. Many related studies have reported the development of this technology for solid ferromagnetic materials and assemblies of ferromagnetic materials, through experimental data models [18][19][20], the probability evaluation model [21], and the magnetic theoretical model. It was found that the SMFD signal around the defect changed depending on the defect types, defect position, and cross-sectional area [17].…”

Section: Introductionmentioning

confidence: 99%

Theoretical Model of Self-Magnetic Flux Leakage and Its Application in Estimating the Depth Direction of a Fatigue Crack

2022

View full text Add to dashboard Cite

In this study, theoretical models were proposed to explain the changes in self-magnetic flux density (SMFD) due to fatigue cracks in the presence and absence of external magnetic fields. Three theoretical models were proposed: rotation domain model (RDM), concentration domain model (CDM), and vertical domain model (VDM), considering the deformation and non-deformation possibilities. To prove the theoretical model, fatigue cracks with different depth angles were fabricated through fatigue testing and EDM processing on the CT specimens. In addition, tunnel magnetoresistance (TMR) sensors were used to evaluate the 3-axis distribution of SMFD. Comparing the simulation and experimental results, similar tendencies of the occurrence and depth angle of fatigue cracks and their effect on the distribution of SMFD were observed. According to the RDM, the distribution of SMFD occurs in the direction of the crack length (y-direction), while the CDM explains that the SMFD does not occur if the fatigue crack is in a direction perpendicular to the surface. In addition, the VDM shows that SMFDs occur in a direction perpendicular to the crack length (x-direction) and the specimen surface (z-direction). Interestingly, these trends agree with the experimental results, which confirms the validity of the theoretical model and thus can be used to estimate the depth direction of a fatigue crack.

show abstract

“…MT is commonly used to detect the surface and subsurface defects of ferromagnetic materials, such as castings, forgings, rolled steel plates, heat treatment parts, and machining and grinding parts. [1][2][3] MT testing is simple and enables fast inspection with high flaw detection and sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Image feature analysis for magnetic particle inspection of forging defects

Hsu

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

Magnetic particle inspection is typically used to detect the magnetic leakage caused by defects. This method is mainly used to detect the surface and subsurface defects of ferromagnetic materials. The conventional detection method involves inspectors performing visual inspection under high-power ultraviolet light. However, the intense ultraviolet light can easily damage the eyes of the inspectors. Furthermore, the aforementioned process is not only time consuming but also susceptible to human errors. Therefore, this study developed an automated optical inspection system to perform magnetic particle inspection. Analysis of several image features revealed that a contour compactness between four and five can be used to distinguish defective and non-defective features effectively. The defect identification ability obtained with several input combinations of image features for neural networks was analyzed. The results revealed that a high identification ability can be achieved for defective features when the input combination of area, mean width, and compactness is used.

show abstract

Magnetic flux leakage technique to detect loss in metallic area in external post-tensioning systems

Cited by 21 publications

References 13 publications

Risk-Based Selection of Inspection Method for External Post-Tensioning System of Bridges

Risk-Based Selection of Inspection Method for External Post-Tensioning System of Bridges

Theoretical Model of Self-Magnetic Flux Leakage and Its Application in Estimating the Depth Direction of a Fatigue Crack

Image feature analysis for magnetic particle inspection of forging defects

Contact Info

Product

Resources

About