Correlation between Crack Growth Rate and Magnetic Memory Signal of X45 Steel

Xing, Hai Yan; Wang, Ri Xin; Xu, Min; Zhang, Jiazhong

doi:10.4028/www.scientific.net/kem.353-358.2293

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…In graphical observation, the rate of crack growth, da/dN, was increased simultaneously with the increasing of magnetic flux leakage towards the surface of the metal with the R-Squared values in the range of 0.7387 to 0.8863 respectively. It can also be clearly seen that the patterns of the curves (for all specimens) showed an identical trend, with a sigmoid shape (Xing et al 2007).…”

Section: The Formation Of Magnetic Signalsmentioning

confidence: 60%

“…Furthermore, Dong et al (2010a) discussed MMM signal characteristics in the tension-tension fatigue testing of notched plate specimens; and reported that the MMM signals are intensively affected by many factors, such as different load types, machining processes, heat treatment conditions, and extra magnetic fields, which prevent MMM testing from being widely used in practical projects. This was further enhanced by Xing et al (2007) in studying the correlation between the crack growth rate, da/dN, and magnetic memory signal Hp(y) through a three-point bending fatigue testing. Wang et al (2012) also reviewed the fundamentals of MMM technology as an effective method in assessing the early damage and defects by detecting the surface of metal depth of up to several millimeters with a maximum measuring velocity of up to several meters per second.…”

Section: Introductionmentioning

confidence: 99%

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Fatigue crack effect on magnetic flux leakage for A283 grade C steel

Ahmad¹,

Arifin²,

Abdullah³

et al. 2015

Steel Compos. Struct.

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This paper presents the characterization of fatigue crack in the A283 Grade C steel using the MMM method by identifying the effects of magnetic flux leakage towards the crack growth rate, da/dN, and crack length.The previous and current research on the relation between MMM parameters and fatigue crack effect is still unclear and requires specific analysis to validate that. This method is considered to be a passive magnetic method among other Non-Destructive Testing (NDT) methods. The tension-tension fatigue test was conducted with a testing frequency of 10 Hz with 4 kN loaded, meanwhile the MMM response signals were captured using a MMM instrument. A correlation between the crack growth rate and magnetic flux leakage produces a sigmoid shape curve with a constant values which present the gradient, m value is in the ranges of 1.4357 to 4.0506, and the y-intercept, log C in the ranges of 4×10 -7 to 0.0303. Moreover, a linear relation was obtained between the crack length and magnetic flux leakage which present the R-Squared values is at 0.830 to 0.978. Therefore, MMM method has their own capability to investigate and characterize the fatigue crack effects as a main source of fracture mechanism for ferrous-based materials.

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Section: The Formation Of Magnetic Signalsmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Fatigue crack effect on magnetic flux leakage for A283 grade C steel

Ahmad¹,

Arifin²,

Abdullah³

et al. 2015

Steel Compos. Struct.

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show abstract

“…It can be observed from the graphs in Figure 4, that the abnormal magnetic peak (drastic change) occurred in the middle of the scanning distances (45 mm to 55 mm), which appears under the notch areas of the specimen. Indeed, this mechanism is either plastically induced by crack closure or crack rate retardation associated with the plastic zone ahead of a crack tip, in which the tensile overload cycle leads to the crack tip sharpening and the crack rate increasing (Wu et al, 2010;Xing et al, 2007). Also, the signals of Hp(y) and dHp/dx in Figure 4(a) show the standard magnetic signals with weak changes in specific areas on the surface of a specimen.…”

Section: Probabilistic Approachmentioning

confidence: 99%

The probabilistic analysis of fatigue crack effect based on magnetic flux leakage

Ahmad

Arifin

Abdullah

et al. 2019

IJRS

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In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72-0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.

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“…As displayed, the pattern of this plot is similar to that of the second region in Figure 2 Hypothetically, dH(y)/dx and ∆K are similar in the sense that they both indicate the state of stress during fatigue crack growth. Xing et al [11] and Ahmad et al [19] investigate relationship between ∆K and H(y) and it was stated that H(y) variation reflects the change of stress intensity factor ∆K during the whole crack growth process and linear relation was represented between ΔK and H(y) graph. Figure 6 illustrates the investigation conducted on the relationship between dH(y)/dx and ∆K.…”

Section: Relationship Between Magnetic Flux Gradient Signals Dh/dx Amentioning

confidence: 99%

“…A substantial number of studies have been performed in efforts to link the MMM signals to fatigue crack growth parameters. Xing et al [11] investigated the association between the crack growth rate da/dN and the MMM regular component signal H(y). It was observed that the H(y) increased in tandem with the rise of da/dN while the correlation curve between H(y) and da/dN exhibited a sigmoidal figure.…”

Section: Introductionmentioning

confidence: 99%

Magnetic flux gradient observation during fatigue crack propagation: A case study of SAE 1045 carbon steel used for automotive transmission parts

et al. 2016

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Abstract. The objective of this study is to evaluate the application of the metal magnetic memory (MMM) technique for investigations on fatigue crack propagation in a ferromagnetic material. Fatigue failure caused by stress concentration is serious in practical engineering. However, early fatigue damages cannot be detected by using traditional nondestructive testing (NDT) methods. Therefore this paper study about NDT method called metal magnetic memory (MMM) that has potentials for evaluating the fatigue damage at the early damage and critical fracture stages. While its capacity to evaluate the distribution of self-magnetic leakage field signals on the component's surface is well-established, there remains a need to scrutinize the physical mechanism and quantitative analysis aspects of this method. To begin with, a fatigue test involving a loading of 7kN was conducted on a SAE 1045 carbon steel specimen. This material is frequently used in the manufacturing of automotive transmission components that include the axle and spline shaft. MMM signals were measured along a scanning distance of 100 mm and analysed during the propagation stage. Other than revealing that the value of the magnetic flux gradient signals dH(y)/dx increased in tandem with the crack length, the results also led to the detection of the crack growth location. It was anticipated that the dH(y)/dx value will also exhibit an upward trend with a rise in the fatigue growth rate of da/dN. A modified Paris equation was utilized to correlate dH(y)/dx with da/dn through the replacement of the stress intensity factor range ∆K. This resulted in the log-log plot of da/dN versus dH(y)/dx portraying an inclination similar to the log-log plot of da/dN versus ∆K. A linear relationship was established between dH(y)/dx and ∆K with the R 2 value as 0.96. Players in the automotive industry can benefit from the disclosure that dH(y)/dx can effectively replace ∆K for the monitoring of fatigue crack growth behaviour.

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Correlation between Crack Growth Rate and Magnetic Memory Signal of X45 Steel

Cited by 6 publications

References 2 publications

Fatigue crack effect on magnetic flux leakage for A283 grade C steel

Fatigue crack effect on magnetic flux leakage for A283 grade C steel

The probabilistic analysis of fatigue crack effect based on magnetic flux leakage

Magnetic flux gradient observation during fatigue crack propagation: A case study of SAE 1045 carbon steel used for automotive transmission parts

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