CN102445491A - Method for evaluating stress concentration degree of remanufactured blank by using self-emission magnetic signal - Google Patents

Abstract

The invention discloses a method for quantitatively evaluating the stress concentration degree of a waste and used ferromagnetic part by using a self-emission magnetic signal, belonging to the technical field of nondestructive detection. The method comprises the following steps of: manufacturing a test piece by using a material which is the same as that of the tested waste and used ferromagnetic part, designing different tests for corresponding bending, torque, impact, fatigue and the like, and scanning a stress concentration region on the surface of the test piece according to a fixed lift-off value by using a magnetic sensor in the testing process to obtain a self-emission magnetic signal of the stress concentration region; computing the obtained signal, extracting multiple characteristic parameters, and establishing a mapping relation model between the characteristic value of the self-emission magnetic signal of the stress concentration region and the stress concentration degree by using a nerve network; and detecting a self-emission magnetic signal of a potential dangerous region on the surface of a tested member by using the same lift-off value, and quantitatively evaluating the stress concentration degree of a tested ferromagnetic test piece according to the mapping relation model between the characteristic value of the self-emission magnetic signal and the stress concentration degree. The evaluation reliability of stress concentration with a metal magnetic memory technology is enhanced, operation is simple and convenient, and high repeatability is achieved.

Description

A Method for Evaluating Stress Concentration of Remanufactured Blanks Using Spontaneous Emission Magnetic Signals

technical field

The invention relates to a method for evaluating the stress concentration degree of remanufactured blanks by using spontaneously emitted magnetic signals, and belongs to the technical field of nondestructive testing.

Background technique

Remanufactured blanks are the production objects of remanufacturing, and they are waste mechanical parts that have gone through a service cycle. These waste parts may be damaged or even defective during service. Before remanufacturing, the degree of damage of the remanufactured blank must be evaluated to determine whether it has remanufacturing value. Only waste parts with remanufacturing value can be remanufactured.

For remanufactured blanks that have generated macroscopic defects, conventional nondestructive testing methods, such as ray, ultrasonic, eddy current, magnetic force, penetrant testing, etc., can be found, but these methods cannot diagnose the early hidden damage of remanufactured blanks. At present, remanufacturing enterprises mainly use magnetic particle, ultrasonic, osmotic, hydraulic and other flaw detection technologies to detect dangerous defects such as cracks in waste parts. If no defects are found, these waste parts are considered to have remanufacturing value and can be remanufactured, which makes waste parts with no macro defects but early damage enter the remanufacturing process, burying quality hidden dangers.

Due to the complexity and concealment of early damage, it is very difficult to non-destructively evaluate the early damage degree of remanufactured blanks. Metal magnetic memory technology is an advanced non-destructive testing method formed in the late 1990s. It uses the spontaneous magnetic emission signals generated spontaneously by ferromagnetic materials under load excitation during service to find potential stress concentration sites. attracted attention for its potential. Russian scholars, as the original creators of metal magnetic memory technology, proposed to use the gradient value of the normal component of the magnetic signal to evaluate the stress concentration of ferromagnetic materials, and established the empirical formula (1) as follows:

$\mathrm{<span\; class="notranslate">\; K</span>}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}}<span\; class="notranslate">\; |</span>}{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In the formula (1): ΔH _p represents the change of the normal component of the spontaneously emitted magnetic signal on the surface of the ferromagnetic material; Δl _k represents the length detected by the corresponding probe.

At present, in the engineering field and academic field, this formula is used as the basis to evaluate the danger degree of the stress concentration area of ferromagnetic parts. However, for different ferromagnetic components, the correlation between its chemical composition, geometric size, service environment, service load and many other influencing factors and the variation law of spontaneous magnetic emission signals has not yet been clarified, and there is a lack of calibration standards for the degree of stress concentration. According to the formula (1) It is only possible to qualitatively evaluate the degree of stress concentration of similar parts, and it is difficult to quantitatively compare the degree of stress concentration of ferromagnetic remanufactured blanks with different structures, functions and service conditions.

Among the existing technologies, there is only the Chinese invention patent with application number 200710119911.6 and publication number CN101122578A—a magnetic memory detection method for fatigue cracks and stress concentration of ferromagnetic metal components. A magnetic stress concentration factor is proposed to characterize the degree of stress concentration of ferromagnetic materials The method uses the ratio of the maximum value to the minimum value of the horizontal component H _p (x) signal magnetic field intensity of the spontaneous emission magnetic signal as the comparison standard. This method is still a qualitative evaluation method of stress concentration and is not suitable for comparison of different parts.

Contents of the invention

The purpose of the present invention is to invent a novel detection method for quantitatively evaluating the stress concentration degree of ferromagnetic parts under different service conditions by utilizing spontaneous emission magnetic signals.

The present invention provides a series of standard stress concentration factor test pieces, which are tested under different service conditions to obtain the mapping relationship between the characteristic parameters of the spontaneous emission magnetic signal and the stress concentration factor, and use this mapping relationship to evaluate the waste The stress concentration degree of potentially dangerous parts of ferromagnetic parts is used to quantitatively evaluate the stress concentration degree of remanufactured blanks by using spontaneous magnetic emission signals.

The present invention realizes through following technical scheme:

A method for quantitatively evaluating the stress concentration degree of waste ferromagnetic parts by using spontaneous magnetic emission signals, characterized in that the method includes the following steps:

1) Use the same material as the scrap ferromagnetic parts to be tested to make a series of standard test pieces of stress concentration coefficient, and perform final treatment before use according to the surface quality and heat treatment specifications of the new scrap ferromagnetic parts to be tested;

2) The magnetic sensor is perpendicular to the surface of the standard test piece, and according to the fixed lift-off value, scans the stress concentration part on the surface of the standard test piece, and obtains the spontaneous magnetic emission signal of the detection surface of the test piece in the initial state;

3) According to the service condition requirements of the ferromagnetic parts to be tested, one or several different test types of bending, torsion, impact and fatigue are designed, and the stress concentration factor standard test piece is tested. During the test, the magnetic sensor is used to vertically test the surface of the test piece , according to the same fixed lift-off value in step 2), scan the stress concentration area on the surface of the test piece to obtain the spontaneous magnetic emission signal of the stress concentration area; the determination of the number of detections is determined according to the design life of the tested part; repeat the above steps until the standard specimen damage;

4) The signal measured by the magnetic sensor in the above steps is calculated and processed to extract one or both of the horizontal component H _p (x) or the normal component H _p (y) or the tangential component H _p (z) of the spontaneous emission magnetic signal One or three kinds of characteristic parameters, and the neural network is used to establish the mapping relationship model between the characteristic value of the spontaneous magnetic signal in the stress concentration area of the standard specimen and the degree of stress concentration;

5) Using the magnetic sensor used in step 2), according to the same lift-off value as in step 2), detect the spontaneous magnetic emission signal of the potentially dangerous area on the surface of the ferromagnetic part under test, according to the characteristic value of the spontaneous magnetic emission signal determined in step 4) The mapping relationship with the stress concentration degree can quantitatively evaluate the stress concentration degree of the tested ferromagnetic specimen;

The above-mentioned method of measuring the spontaneous magnetic emission signal is to measure the standard test piece and the ferromagnetic part under test in an unloaded state.

The magnetic sensor used to measure the one-dimensional or two-dimensional or three-dimensional magnetic signal of the ferromagnetic material's own leakage field, that is, the normal component H _p (y) signal, the horizontal component H _p (x ) signal or tangential component H _p (z) signal or one of two or three signals, the measurement accuracy is equal to or higher than 1A/m.

The method determined by the present invention utilizes the ferromagnetic material self-emission magnetic signal to realize the quantitative evaluation of the degree of stress concentration, without adding an excitation magnetic field and a demagnetization device to the waste ferromagnetic parts to be tested, and does not need any pretreatment on the surface of the waste parts.

Description of drawings

Fig. 1 is the stress concentration standard test piece and detection line layout that the present invention adopts

Fig. 2 is the surface two-dimensional magnetic signal distribution characteristic in the stress concentration standard specimen fatigue test process that the present invention adopts

Detailed ways

The present invention realizes by following measures:

The material of the tested component is 42CrMo steel, and the self-emission magnetic signal detection instruments are EMS-2003 metal magnetic memory detector (detection of normal component H _p (y) signal) and RM-1 type magnetic memory detector (detection of horizontal component H _p (x) signal).

1) Select the ferromagnetic material 42CrMo steel with the same material as the tested component, and make stress concentration factor test pieces of five prefabricated cuts with stress concentration factor K _t = 1 to 5 according to national standards, and the upper limit of surface roughness R _a It is 0.4μm, heated to 860°C, held for 30 minutes, oil quenched, then tempered at 540°C for 2 hours, cooled to below 200°C with the furnace and air-cooled to obtain a pure initial magnetic state.

At the prefabricated incisions on both sides of the specimen surface, each detection line is spaced 1 mm apart, and a total of 10 parallel detection lines are arranged to cover the prefabricated incisions. The detection line length is 100mm, as shown in Figure 1.

2) The magnetic sensor used is based on the Hall element, which can collect the two-dimensional signal of the surface stray magnetic field, that is, the normal component H _p (y) signal and the horizontal component H _p (x) signal of the spontaneous emission magnetic signal, and the detection accuracy is 1A/m. The sensor is perpendicular to the surface of the test piece, with a lift-off value of 1 mm, and scans each detection line in a straight line (the scanning direction is shown by the arrow in Figure 1), collects the two-dimensional signal of the stray magnetic field on the surface of the test piece in the initial state, and obtains H _p (x) and H _p (y) signal distributions.

3) Apply constant-amplitude tension-compression fatigue load to the stress concentration standard specimen, and set the maximum stress σ _max = 160MPa, stress ratio R = -1, and frequency f = 30Hz according to the service load spectrum of the real part. Load to the cycle times of the initial, middle and late stages of the fatigue life of the standard specimen, unload and remove the specimen respectively, place the specimen on a non-magnetic three-dimensional platform along the north-south direction of the geomagnetic field, and control the magnetic field by the three-dimensional electronically controlled scanning frame. The sensor detection line moves in a fixed way to obtain the two-dimensional signal on the surface of the stress concentration part of the specimen, and the signal is sent to the computer for processing to obtain the distribution of the normal component of the stray magnetic field on the surface under the number of cycles. Repeat the above steps to obtain the distribution law of the number of fatigue cycles and the two-dimensional signal of the stray magnetic field on the surface of the specimen under different stress concentration factors (as shown in Figure 2), until fatigue cracks are initiated on the specimen.

4) Use Matlab software to extract two characteristic parameters of the peak-to-peak value and peak-to-peak slope value of the H _p (y) signal, and three characteristic quantities of the H _p (x) signal, such as peak width, peak height and kurtosis factor, and use these five signals The characteristic quantity is the input vector to establish a three-layer BP network model, the number of neurons in the output layer is 1, which is the stress concentration value of the specimen, and the BP neural network model of the mapping relationship between the characteristic quantity of the spontaneous magnetic signal and the stress concentration degree is established.

5) Using the magnetic sensor used in step 2), according to the same lift-off value as in step 2), detect the spontaneous magnetic emission signal of the potentially dangerous area on the surface of the ferromagnetic part under test, according to the two-dimensional magnetic signal characteristic value determined in step 4) The neural network model of the degree of stress concentration is used to quantitatively evaluate the degree of stress concentration of the tested ferromagnetic specimen.

Claims (2)

1. method of utilizing the waste and old ferromagnetic part stress concentration degree of self-emission magnetic signal quantitative evaluation is characterized in that this method comprises following each step:

1) standard specimen of the material series SCF of employing and the identical material of tested waste and old ferromagnetic part, the final processing before surface quality when dispatching from the factory according to tested waste and old ferromagnetic part new product and heat treatment regime require to use;

2) the vertical standard specimen of Magnetic Sensor surface, according to fixing lift-off value, the stress on scanning standard test specimen surface is concentrated the position, obtains that test specimen detects surperficial self-emission magnetic signal under the original state;

3) according to the requirement of tested ferromagnetic part service condition; Design is corresponding crooked, reverse, impact, tired one or more different tests types; Carry out the test of SCF standard specimen, utilize the vertical test specimen of Magnetic Sensor surface in the process of the test, according to step 2) identical fixedly lift-off value; The region of stress concentration on scanning test specimen surface, the self-emission magnetic signal of acquisition region of stress concentration; Normal root is definite according to the designed life of tested part really to detect number of times; Repeat above-mentioned steps, destroy until standard specimen;

4) signal that in above-mentioned steps, records of Magnetic Sensor extracts self-emission magnetic signal horizontal component H through computing _p(x) or normal component H _p(y) or tangential component H _pOne of (z) or the characteristic parameter of two kinds or three kinds, adopt neural network to set up the eigenwert of standard specimen region of stress concentration self-emission magnetic signal and the mapping relations model of stress concentration degree;

5) adopt step 2) used Magnetic Sensor; According to step 2) identical lift-off value; Detect the self-emission magnetic signal in tested ferromagnetic piece surface potential danger zone; According to the self-emission magnetic signal characteristic quantity of confirming in the step 4) and the mapping relations of stress concentration degree, the stress concentration degree of the tested ferromagnetic test specimen of quantitative evaluation;

The metering system of above-mentioned self-emission magnetic signal is that standard specimen and tested ferromagnetic part are measured under unloaded state.

2. a kind of method of utilizing the waste and old ferromagnetic part stress concentration degree of self-emission magnetic signal quantitative evaluation according to claim 1; It is characterized in that: the Magnetic Sensor of use is measured one of two-dimentional or three-dimensional or two kinds of perhaps three kinds the magnetic signals of the one dimension of the own stray field of ferromagnetic material, is normal component H _p(y) signal, horizontal component H _p(x) signal or tangential component H _p(z) one of signal or two kinds or three kinds of signals, measuring accuracy is equal to or higher than 1A/m.

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