Characteristics of Metal Magnetic Memory Testing of 35CrMo Steel during Fatigue Loading

Fan, Jun; Wu, Shengnan; Dai, Hailu; Liu, Shujie

doi:10.3390/met8020119

Cited by 23 publications

(15 citation statements)

References 35 publications

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“…Sensing elements able to monitor surface stresses in steels can be those monitoring localized changes of sound velocity, including the use of non-linear acoustics [11], electromagnetic properties such as eddy currents for resistivity and impedance determination [12], optical properties using the Kerr effect [13], as well as magnetic properties like surface permeability in the magnetic stress calibration curve (MASC) technique [14] and the magnetic memory method (MMM) [15], or magnetic Barkhausen noise method [16]. The sensing elements used in acoustic techniques offer a spatial resolution in the order of cm and may be used in industrial conditions.…”

Section: Introductionmentioning

confidence: 99%

Sensor to Monitor Localized Stresses on Steel Surfaces Using the Magnetostrictive Delay Line Technique

Liang

Angelopoulos

Lepipas

et al. 2019

Sensors

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In this paper, a new type of force sensor is presented, able to monitor localized residual stresses on steel surfaces. The principle of operation of the proposed sensor is based on the monitoring of the force exerted between a permanent magnet and the under-test steel which is dependent on the surface permeability of the steel providing a non-hysteretic response. The sensor’s response, calibration, and performance are described followed by a discussion concerning the applications for steel health monitoring.

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Section: Introductionmentioning

confidence: 99%

Sensor to Monitor Localized Stresses on Steel Surfaces Using the Magnetostrictive Delay Line Technique

Liang

Angelopoulos

Lepipas

et al. 2019

Sensors

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“…Huang [14] and Li [15] investigated the relationship between crack length and gradient of H y by carrying fatigue bending tests. Chowdhury [16] and Hu [17] also investigated the mechanisms of fatigue crack growth and studied the magnetic field variation. In previous studies, the variations of magnetic signals in different stages of the fatigue process were not deeply discussed or fully understood.…”

Section: Introductionmentioning

confidence: 99%

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

Zhou

Fan

et al. 2019

Metals

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To monitor fatigue crack initiation and propagation, and to judge the fatigue damage status of ferromagnetic material, fatigue bending tests of four-point single edge notch bend (SENB4) specimens were carried out. Metal magnetic memory signals were measured during the whole fatigue process. The results showed that the fatigue process could be divided into four stages by observing the morphology of the fracture surface. With the increase of fatigue loading cycles, the tangential component of the magnetic field (Hx) and the normal component of the magnetic field (Hy) increased. At the notch Hx presented a “trough” shape and had a maximum value at the midpoint, while Hy at the notch rotated clockwise around the midpoint. Compared with the tangential characteristic parameters, the variation of normal characteristic parameters (i.e., maximum gradient value of Hy (Ky-max) and the variation range of Hy at the notch (∆Hyn), with the fatigue loading cycles are more similar to the variation of fatigue crack length with loading cycles), both Ky-max and ∆Hyn had a good linear relationship with fatigue crack length. Plastic deformation accumulated on both sides of the fatigue crack, and metal magnetic memory (MMM) signals measured from the specimens were able to indicate the location of the fatigue crack and the variation of the fatigue crack length. Furthermore, the distribution of magnetic signals was analyzed according to the theories of stress magnetization and magnetic flux leakage.

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“…Monitoring the fatigue damage of the civil engineering structures has been actively investigated [ 6 , 7 , 8 ]. The current methods for monitoring the fatigue damage mainly include Barkhausen noise measurements [ 9 , 10 , 11 , 12 ], X-ray tomography [ 13 , 14 , 15 , 16 ], metal magnetic memory (MMM) testing method [ 17 , 18 , 19 , 20 , 21 ], acoustic emission (AE) [ 22 , 23 , 24 , 25 ], ultrasonic and nonlinear ultrasonic techniques [ 26 , 27 , 28 , 29 , 30 ], among others. Barkhausen noise measurements were used to evaluate fatigue damage of engineering structural steel structures [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…Marrow et al demonstrated the feasibility of imaging short fatigue cracks with high resolution synchrotron X-ray tomography [ 13 , 14 ]. The metal magnetic memory testing method is a novel nondestructive testing technology developed to monitor crack propagation and predict fatigue life [ 17 , 18 ]. The acoustic emission (AE) monitoring has been developed as an effective method for the detection, location and monitoring of fatigue damage in the metal structures by monitoring the acoustic signature of the fatigue crack during the opening/closing process [ 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Fatigue Damage of Modular Bridge Expansion Joints Using Piezoceramic Transducers

Jiang

Zhang

Wang

et al. 2018

Sensors

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Modular bridge expansion joints (MBEJs) are commonly used in bridges and are often subjected to fatigue damages, which necessitate fatigue monitoring of MBEJs to ensure the reliable operation of the bridges. In this paper, a stress wave based active sensing approach using piezoceramic transducers is developed to monitor the fatigue damage of MBEJ. A MBEJ involves mainly center beam, edge beam, support bar, support box, sliding bearing, sliding spring, elastomeric strip seal, full-penetration weld and reinforcing plate. In practice, for a MBEJ, the part that is most prone to fatigue damage is the full-penetration weld between the center beam and the support bar. In this paper, a specimen, which is the full-scale center-beam/support-bar (CB/SB) assembly, was designed and fabricated to facilitate the experimental study. The assembly mainly includes center beam, support bar, reinforcing plate, and full-penetration weld. The lead zirconate titanate (PZT) transducer bonded on the support bar was used as the actuator and the PZT transducer mounted on the center beam was as the sensor. Dial indicators were utilized to measure the vertical displacement of the center beam. Two series of tests, including static test, and fatigue test, were performed on the specimen in an alternating fashion. Based on the number of cyclic loading, the experiment was divided into six different stages: 0th cycle (the healthy state), 0.8 million cycles, 1.6 million cycles, 2.4 million cycles, 3.2 million cycles, and 4 million cycles. The signals received by the PZT sensor were analyzed with the help of wavelet packet analysis. In addition, the structure stiffness also was considered as a comparative approach in this paper. Experimental results show that during the fatigue test, the structure stiffness decreases with the number of cycle loading. However, the method can only obtain the fatigue damage impact on the entire structure, and cannot determine the fatigue damage degree of a certain weld. On the other hand, the proposed method can accurately monitor the fatigue damage degree of full-penetration welds. The research results show that the developed piezoceramic enabled active sensing approach can monitor and estimate the fatigue damage in MBEJ in real-time.

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Characteristics of Metal Magnetic Memory Testing of 35CrMo Steel during Fatigue Loading

Cited by 23 publications

References 35 publications

Sensor to Monitor Localized Stresses on Steel Surfaces Using the Magnetostrictive Delay Line Technique

Sensor to Monitor Localized Stresses on Steel Surfaces Using the Magnetostrictive Delay Line Technique

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

Monitoring Fatigue Damage of Modular Bridge Expansion Joints Using Piezoceramic Transducers

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