CN100573132C - Utilize the method for variated magnetic signal monitoring ferromagnetic material fatigue crack expansion - Google Patents

Abstract

A kind of method of utilizing the expansion of variated magnetic signal monitoring ferromagnetic material fatigue crack belongs to technical field of nondestructive testing.The present invention relates to a kind of method of utilizing variated magnetic signal monitoring ferromagnetic material fatigue crack expansion, make standard sample with tested member material, centre burst that condition of heat treatment is identical; In torture test, behind the circulation pre-determined number, press the fixedly centre burst district of lift-off value scanning standard specimen, obtain the surface stray magnetic field normal component H in scanning district with Magnetic Sensor _p(y) signal records the length 2a of centre burst; Extract the maximal value Δ H at the spontaneous variated magnetic signal peak of fatigue crack generation _p(y) _Max, as the detection threshold under this cycle index; To Δ H _p(y) _MaxCarry out linearity with 2a and fit, get Δ H _p(y) _Max-2a relational expression; Detect tested member with above-mentioned Magnetic Sensor by identical lift-off value, with measured Δ H _p(y) _MaxWith the detection threshold contrast, according to Δ H _p(y) _Max-2a linear relation is known the crack Propagation process.The present invention is easy and simple to handle, and testing result is accurate, can be in dynamic monitoring crack propagation under the unloaded state.

Description

A Method for Monitoring Fatigue Crack Propagation of Ferromagnetic Materials Using Variable Magnetic Signals

technical field

The invention relates to a method for monitoring the expansion of fatigue cracks by using spontaneously generated abnormal signals in the geomagnetic field environment, which is suitable for dynamic quality control of ferromagnetic parts bearing fatigue loads and belongs to the technical field of non-destructive testing.

Background technique

The surface of ferromagnetic materials in the geomagnetic field will spontaneously generate stray magnetic field signals during processing, manufacturing and service, which can be detected by detecting the zero value point of the normal component H _p (y) of the stray magnetic field and combining the maximum value of the magnetic field gradient. Qualitatively judge the location of ferromagnetic material stress concentration, that is, the potential danger area. This is also known as metal magnetic memory detection technology.

The development time of metal magnetic memory detection technology is relatively short, and its microscopic physical mechanism has not yet been clarified. Although a lot of basic research has been carried out on this technology in recent years, it is mostly used in power stations, petroleum, pipelines, pressure vessels and other departments for static defect detection, Semi-quantitative evaluation of residual stress and stress concentration. For example, Chinese patent specification 01123977.8 discloses a method for detecting surface defects of ferromagnetic materials by using the geomagnetic field. After processing, the detection signal is compared with the set defect threshold to determine whether there are surface cracks. , corrosion pits, slag inclusions near the surface, pores and other defects; Chinese patent specification 01143445.7 discloses a magnetic detection method for stress distribution, which uses the linear relationship between geomagnetic signals and internal stress of ferromagnetic materials to measure the stress distribution. Chinese patent specification 200510122191.X discloses a method for diagnosing welding cracks in pipelines using metal magnetic memory detection signals. The wavelet transform theory is used to analyze and process the magnetic memory detection signals to obtain the judgment threshold K and realize rapid non-destructive detection of welding cracks; Chinese patent specification 200510122190.5 announced the use of metal magnetic memory detection technology to determine the stress concentration method of pipeline welding cracks. According to the Gaussian law of magnetic field, the relationship between the internal stress of the pipeline wall and the metal magnetic memory signal is determined, and the maximum value of the stress at the tip of the welding crack is defined as the stress concentration degree of the welding crack. A measure to realize the quantitative evaluation of the stress concentration degree at the tip of the welding crack in the pipeline, etc.

However, there are few reports on the application of metal magnetic memory technology in the field of fatigue life prediction. Only Chinese patent specification 200410067574.7 proposes a method for detecting the remaining fatigue life of an automobile decommissioned crankshaft using eddy current and magnetic memory detection technology. Technically check whether there are cracks in the key parts of the decommissioned crankshaft. If there are no cracks, use metal magnetic memory technology to detect the stress and deformation of this part, and evaluate whether the remaining life is sufficient to maintain the remaining life according to the mapping relationship between the stress and deformation and the remaining life. One life cycle. If there is a crack, it is considered that its remaining fatigue life is not enough to maintain a life cycle, and the magnetic memory technology is no longer used for detection.

For important components with cracks or cracks that are subject to fatigue loads, only acoustic emission technology can realize the dynamic monitoring of crack growth. Although the acoustic emission phenomenon has been discovered as early as the 1950s, it must be loaded when using this technology, and the background noise Problems such as interference limit its practical application. Whether the stray magnetic field signal of the ferromagnetic material itself can be used to monitor the fatigue crack growth of the ferromagnetic material and predict its remaining life has not yet been involved in any literature or patent.

Contents of the invention

The present invention aims to solve the problem that the only existing acoustic emission technology that can realize dynamic monitoring of fatigue crack growth must be loaded when used, and cannot be applied in an unloaded state.

Ferromagnetic components subjected to fatigue loads in the geomagnetic field environment will generate spontaneous stray magnetic field signals on the surface under working conditions, and the stray magnetic field signals will change in the parts where there are fatigue cracks, and with the fatigue As the crack expands, the abnormal signal will gradually increase. The method proposed by the invention realizes the dynamic monitoring of the expansion process of the fatigue crack by detecting the variation signal of the normal component H _p (y) of the stray magnetic field during the fatigue process.

The invention discloses a method for monitoring the growth of fatigue cracks in ferromagnetic materials by using spontaneous variable magnetic signals, which is characterized in that the method includes the following steps:

1) Use the same material as the ferromagnetic component to be tested to make a plate-shaped standard tensile sample with a central penetration crack, and perform final heat treatment on the standard sample according to the heat treatment specification of the component to be tested. The maximum heating temperature of the heat treatment process is Exceeding the Curie point temperature of the material, the surface of the standard test piece can obtain a pure initial magnetic state;

2) The magnetic sensor is perpendicular to the surface of the test piece, according to the fixed lift-off value, along the direction of the vertical center penetration crack, and in a straight line, scan the center penetration crack of the standard test piece line by line along each detection line to obtain the initial state of the test piece The normal component H _p (y) signal of the stray magnetic field on the lower surface;

The lift-off value refers to the distance between the magnetic sensor and the surface of the test piece. The range of fixed lift-off value is 0.5mm～15mm; the distance range between each detection line is 0.01mm～5mm;

3) Set the fatigue test parameters and carry out the fatigue test. After the fatigue cycle reaches the predetermined number N, measure the total length 2a of the central penetration crack, and use the magnetic sensor to scan the central penetration crack of the test piece according to the method described in step 2). Through the crack part, obtain the normal component signal of the stray magnetic field on the surface of the sample under the number of cycles; repeat the above steps until the sample breaks;

4) The magnetic signal measured by the magnetic sensor in the above steps is processed by computer software, and the distribution diagram of the normal component H _p (y) of the surface stray magnetic field under different fatigue cycle times is established;

5) Extract the peak value of the spontaneously variable magnetic signal ΔH p (y ₎ generated at the crack in the center of the specimen from the H _p (y) distribution diagram corresponding to different cycle times N, and take its maximum value ΔH _p (y) _max as the The detection threshold at the number of cycles;

6) Draw the relationship curve between the detection threshold ΔH _p (y) _max and the total length 2a of the central penetrating crack at each number of cycles, and use the least square method to perform linear fitting to obtain the linear relational expression of ΔH _p (y) _max -2a;

7) Use the magnetic sensor used in the above steps to detect the surface H _p (y) signal of the scanned area of the component under test according to the same lift-off value, and compare the measured peak-to-peak peak value ΔH _p (y) _smax with the first 5) Compare the detection thresholds determined in step 1 to judge the fatigue crack length, and obtain the fatigue crack growth process according to the established ΔH _p (y) _max -2a linear relational expression.

In the above method, the measurement of the length 2a of the central penetrating crack adopts a non-magnetic measurement method;

In the above method, the measurement of the normal component H _p (y) of the surface stray magnetic field under the different cycle times is measured under the unloaded state of the specimen;

In the above method, the magnetic sensor used in the method has a measurement accuracy equal to or greater than 1 A/m.

The invention has the advantage that the abnormal magnetic signal generated by the fatigue crack is spontaneously generated in the geomagnetic field environment, and the peak value of the abnormal variation increases continuously with the fatigue crack expansion, which can provide continuous information of the crack change in real time. No external excitation magnetic field and demagnetization device are required, and the abnormal signal remains even after unloading, which can realize dynamic monitoring of crack growth. The method is easy to operate, accurate in detection results and good in repeatability.

Description of drawings

Accompanying drawing 1 is the detection sample of specific embodiment and the schematic diagram of detection line, and wherein 1 is central crack, and 2 is detection line;

Accompanying drawing 2 is the distribution diagram of the surface stray magnetic field normal component H _p (y) of the sample in the specific embodiment of the scan area at different stages of life;

Accompanying drawing 3 is the linear fitting relationship between the detection threshold of the fatigue crack variation signal and the total length of the central crack in the specific embodiment.

Detailed ways

The content of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments. In a specific embodiment, the material of the component is 18CrNiWA steel.

Firstly, the ferromagnetic material 18CrNiWA steel, which is the same material as the tested component, is selected, and a plate-shaped standard tensile test piece with a central penetrating crack is made according to the national standard GB/T6398-2000. The prefabricated central crack is processed by wire cutting technology, and the original length 2a ₀ =12mm (as shown in Figure 1). Carry out final heat treatment on the standard sample according to the heat treatment specification of the tested component, heat to 860°C in a WZC-30 vacuum heat treatment furnace with a vacuum degree of 8×10 ^-1 Pa, keep it warm for 30 minutes, oil quench, and then 180°C Temper and water cool to room temperature. To obtain a pure initial magnetic state on the surface of the standard test piece.

Secondly, define a scanning range of 30 mm × 50 mm on the surface of the test piece with the central crack as the center, and mark 11 detection lines, with an interval of 3 mm between adjacent detection lines, and each detection line is perpendicular to the direction of the central crack (as shown in Figure 1).

EMS-2003 metal magnetic memory detector is adopted, and its magnetic sensor is based on Hall element, and the detection accuracy is 1A/m. The sensor is perpendicular to the surface of the test piece, with a lift-off value of 1mm, and travels in a straight line (the scanning direction is shown in Figure 1), scanning from the first detection line to the 11th detection line line by line, and the scanning length of each detection line is 50mm. Collect the normal component signal of the stray magnetic field on the surface of the specimen in the initial state, and process it with Origin software to obtain the H _p (y) value distribution map in the initial state (as shown in Figure 2a).

The selection of the lift-off value should be determined by considering various factors such as the shape, size, surface quality, and strength of the stray magnetic field of the ferromagnetic component. The lift-off value is small, that is, the sensor is close to the surface, and the detection accuracy is high. In this embodiment, for the sensor we are currently using, the preliminary research results show that when the lift-off value exceeds 10mm, the collected signal will be somewhat distorted, and if the lift-off value exceeds 15mm, it will affect the detection result and lead to misjudgment. A lift-off value of 1 mm was therefore chosen in the specific test.

Then, apply axial tensile fatigue load to the specimen, the fatigue test is controlled by sine wave constant amplitude load, σ _max =260MPa, stress ratio R=0, frequency f=10Hz. After the fatigue load is applied, fatigue cracks will initiate from the two tips of the prefabricated incision, and gradually expand to the edges on both sides of the specimen as the number of cycles increases. After fatigue crack initiation, the total length of the central crack is 2a (see Figure 1). After loading to the predetermined number of cycles, first use the JXD-250B optical reading microscope to read the total length of the central crack 2a online, then unload and remove the test piece, place the test piece on a non-magnetic platform along the north-south direction, and the three-dimensional electronically controlled displacement The magnetic sensor probe of the metal magnetic memory instrument controlled by the station moves in a fixed manner along each detection line, and the H _p (y) data on the surface of each detection line is collected, processed by Origin software, and the H _p (y) distribution under the cycle number is obtained. Repeat the above test steps to obtain the distribution diagrams of the normal component of the stray magnetic field on the surface of the specimen at different life stages (as shown in Figures 2b, 2c, and 2d).

Extract the peak value of the spontaneous variation magnetic signal ΔH p (y) generated at the central crack of the specimen in the H _p (y) distribution diagram corresponding to different cycle times N, and take its maximum value _{ΔH p (} y) _max as the cycle number under the detection threshold. Draw the relationship between the detection threshold ΔH _p (y) _max and the length 2a of the central penetrating crack 1 at each cycle, and use the least square method to perform linear fitting (as shown in Figure 3), and obtain the standard specimen under the above test conditions The linear relationship between the peak-to-peak threshold value of the variation signal ΔH _p (y) _max and the fatigue crack length 2a:

2a=-9.81231+0.29885ΔH _p (y) _max (1)

Finally, the 18CrNiWA steel components in the same heat treatment state were detected, and the detection area was delineated according to the working conditions of the components, so that each determined detection line was perpendicular to the direction of the fatigue crack. After serving for a certain period of time, the unloading is placed along the north-south direction, and the magnetic sensor is lifted away by 1 mm. The detection lines are scanned according to the above method, and the H _p (y) signal on the surface of the component is collected. After processing by Origin software, the fatigue cracks in the detection area are obtained. The maximum value of the variation peak value ΔH _p (y) _max is calculated according to the formula (1) to obtain the fatigue crack length; as a comparison, the A-type display pulse reflection ultrasonic flaw detector is used to detect the fatigue crack length according to the maximum wave height attenuation method. During the service period, it was tested three times, and the data are shown in the table below:

Detection times Detection area ΔH_p(y)_max/(A/m) The fatigue crack length calculated according to formula (1) (mm) Fatigue crack length obtained by ultrasonic testing (mm) First detection (early life) 63 9.015 8.6 Second detection (mid-life) 91 17.383 18.1 The third test (late life) 130 29.038 27.9

Verified by ultrasonic testing, this method has accurate detection results, is easy to operate, and does not require an external excitation magnetic field, which provides a new way for dynamic monitoring of crack growth in the unloaded state.

Claims (4)

1. a method utilizing variable magnetic signal to monitor ferromagnetic material fatigue crack growth, is characterized in that the method comprises the following steps: 1) Use the same material as the ferromagnetic component to be tested to make a plate-shaped standard sample with a central penetration crack, and perform final heat treatment on the standard sample according to the heat treatment specification of the ferromagnetic component to be tested. The maximum heating temperature of the heat treatment process Exceeding the Curie point temperature of the material, the surface of the standard sample can obtain a pure initial magnetic state; 2) The magnetic sensor is perpendicular to the surface of the standard sample, and according to the fixed lift-off value, along the direction of the vertical center penetration crack, in a straight line, scan the center crack of the standard sample line by line along each detection line to obtain the initial state of the standard sample The normal component H _p (y) signal of the stray magnetic field on the lower surface; The range of fixed lift-off value is 0.5mm～15mm; the distance range between each detection line is 0.01mm～5mm; 3) Set the fatigue test parameters, carry out the fatigue test, and measure the central crack length 2a after the fatigue cycle reaches the predetermined number N, use the magnetic sensor to scan the center crack of the standard sample according to the method described in step 2, and obtain Under this number of cycles, the normal component signal of the stray magnetic field on the surface of the standard sample; repeat step 3) until the standard sample breaks; 4) The magnetic signal measured by the magnetic sensor in the above steps is processed by computer software, and the distribution diagram of the normal component H _p (y) of the surface stray magnetic field under different fatigue cycle times is established; 5) Extract the peak value of the spontaneous variation magnetic signal ΔH p (y) generated at the central crack of the standard sample in the H _p (y) distribution diagram corresponding to different cycle times N, and take its maximum value _{ΔH p (} y) _max as The detection threshold under the number of cycles; 6) Draw the curves of the detection threshold ΔH _p (y) _max and the central crack length 2a at each number of cycles, and use the least square method to perform linear fitting to obtain the linear relational expression of ΔH _p (y) _max -2a; 7) Use the magnetic sensor used in the above steps to detect the H _p (y) signal on the surface of the scanned area of the measured component according to the same lift-off value, and compare the measured peak-to-peak peak value ΔH _p (y) _smax with the first 5) Compare the detection thresholds determined in step 1 to judge the fatigue crack length, and obtain the fatigue crack growth process according to the established ΔH _p (y) _max -2a linear relational expression. 2. The method according to claim 1, characterized in that: the measurement of the central crack length 2a adopts a non-magnetic measurement method. 3. The method according to claim 1, characterized in that: the measurement of the normal component H _p (y) of the surface stray magnetic field under different cycle times is measured by a standard sample in an unloaded state. 4. The method according to claim 1, characterized in that the measurement accuracy of the magnetic sensor used in the method is equal to or greater than 1A/m.

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