CN114114103A - Material force magnetic characteristic parameter determination method for strong and weak magnetic detection - Google Patents
Material force magnetic characteristic parameter determination method for strong and weak magnetic detection Download PDFInfo
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Abstract
The invention relates to the technical field of nondestructive testing, in particular to a method for determining material force magnetic characteristic parameters for strong and weak magnetic testing, which is characterized in that a hysteresis loop I under different stresses and a hysteresis loop II of a non-stressed state sample are approximated by adopting a particle swarm optimization, and J-A model parameters when the mean square error of data on two curves is smaller than a set value or is minimum are the material force magnetic characteristic parameters. The method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection can determine the force magnetic characteristic parameters of materials in strong and weak magnetic detection, the force magnetic characteristic parameters calculated by the method are used in a J-A model, accurate magnetic hysteresis loops of the materials under different stresses can be determined, and the stress in the strong and weak magnetic detection can be identified by using the relationship between the stress and the magnetic hysteresis loops, so that the method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection has a very wide engineering application prospect.
Description
Technical Field
The invention relates to the technical field of nondestructive testing, in particular to a method for determining material force magnetic characteristic parameters for strong and weak magnetic testing.
Background
The strong and weak magnetic detection technology is a novel nondestructive detection technology, integrates research contents in multiple fields of ferromagnetism, nondestructive detection, metal histology and the like, supports non-contact online detection, does not need to preprocess materials before detection, does not influence material performance after detection, has obvious detection signals, can effectively identify stress and the like, and is applied to engineering projects such as in-pipeline detection and the like.
The strong and weak magnetic detection comprises strong magnetic detection and weak magnetic detection. The signal detected by the strong magnetic part is a defect signal, and the signal detected by the weak magnetic part is a composite signal of a defect and stress. Therefore, the strong magnetic detection and the weak magnetic detection are comprehensively analyzed, namely, the magnetic signal generated by the stress can be decoupled, and the detection means is called as strong and weak magnetic detection. Obviously, the strong and weak magnetic detection can not only detect the macroscopic defects of the ferromagnetic material, but also detect the early damage of the ferromagnetic material caused by stress, and has very wide engineering application prospect. However, the accuracy of the material force magnetic characteristic parameters in the strong and weak magnetic detection directly affects the accuracy of drawing the material hysteresis loop, and further affects the accuracy of stress identification. Therefore, the determination of the material force magnetic characteristic parameter is a crucial loop in strong and weak magnetic detection.
In the process of effectively identifying and quantitatively detecting the stress in the existing strong and weak magnetic detection, errors caused by inaccurate force-magnetic characteristic parameters of ferromagnetic materials exist, and the errors finally cause the deviation of a stress identification result and are not beneficial to the quantitative detection of the stress.
In the prior art, a hysteresis loop of a material can be drawn according to a model, and preliminary identification can be performed on stress according to the hysteresis loop. However, the force-magnetic characteristic parameters used in the process of calculating the model are fixed parameters, and the parameters are not recalculated according to the material properties, so that the stress identification in the strong and weak magnetic detection process has deviation from the actual stress, and the engineering application of the strong and weak magnetic detection is limited.
Disclosure of Invention
The invention provides a method for determining the material force-magnetic characteristic parameters for strong and weak magnetic detection, which overcomes the defects of the prior art and can effectively solve the problem that the stress identification result has errors in the processes of effectively identifying and quantitatively detecting the stress in the strong and weak magnetic detection; the method can accurately determine the force-magnetic characteristic parameters of the material, and provides a basis for accurately identifying the stress by strong and weak magnetic detection.
The technical scheme of the invention is realized by the following measures: a method for determining the magnetic characteristic parameters of a material force for strong and weak magnetic detection comprises the following steps:
firstly, calculating the relationship between the magnetization intensity of a pipeline sample to be measured and the intensity of an external magnetic field under different stresses by using a J-A model;
secondly, acquiring a hysteresis loop I under different stresses according to the relationship between the external magnetic field strength and the magnetization strength calculated in the first step;
thirdly, intercepting a pipeline sample to be tested, and testing a hysteresis loop II of the intercepted pipeline sample to be tested in a stress-free state through a hysteresis loop test;
and fourthly, approximating the obtained hysteresis loop I and the hysteresis loop II by adopting a particle swarm optimization to obtain a J-A model parameter when the mean square error of data on the two curves is smaller than a set value or the minimum value, wherein the parameter is a material force magnetic characteristic parameter.
The following is further optimization or/and improvement of the technical scheme of the invention:
in the fourth step, the particle swarm algorithm approximation method is as follows: and approximating the calculated data of the J-A model with the experimental data acquired by the hysteresis loop test, solving the mean square error of the calculated data and the experimental data, and outputting the force-magnetic characteristic parameters of the J-A model when the mean square error is smaller than a set value or the mean square error is minimum.
And when the mean square error is not less than the set value or does not reach the minimum value, continuing to adopt the particle swarm optimization to carry out approximation until the mean square error is less than the set value or reaches the minimum value or the approximation calculation times reach the calculation time set value.
And a fifth step of substituting the parameters obtained in the fourth step into the J-A model to determine the relationship between different stresses and the hysteresis loop of the material so as to identify the stress in strong and weak magnetic detection.
The method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection can determine the force magnetic characteristic parameters of materials in strong and weak magnetic detection, the force magnetic characteristic parameters calculated by the method are used in a J-A model, accurate magnetic hysteresis loops of the materials under different stresses can be determined, and the stress in the strong and weak magnetic detection can be identified by using the relationship between the stress and the magnetic hysteresis loops, so that the method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection has a very wide engineering application prospect.
Drawings
FIG. 1 is a flow chart of a method for determining the force-magnetic characteristic parameters of a material for strong and weak magnetic detection according to the present invention.
FIG. 2 is a flow chart of a J-A model calculation subroutine.
FIG. 3 is a flow chart of particle swarm optimization parameter approximation.
FIG. 4 is a graph showing the results of calculating magnetization curves for different stresses using the magnetomechanical property parameters of the material obtained in example 5.
FIG. 5 is a graph showing the results of hysteresis loops of different stresses calculated by using the parameters of the magnetomechanical properties of the material obtained in example 5.
In fig. 4 to 5, the abscissa is the intensity of the external magnetic field and the ordinate is the magnetization of the material.
Detailed Description
The present invention is not limited by the following examples, and specific embodiments may be determined according to the technical solutions and practical situations of the present invention.
The model or algorithm used in the present invention is well known in the art, and the J-a model is (Jiles Atlierton) model, for example, unless otherwise specified.
The invention is further described below with reference to the following examples:
example 1: as shown in fig. 1, the method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection comprises the following steps:
firstly, calculating the relationship between the magnetization intensity of a pipeline sample to be measured and the intensity of an external magnetic field under different stresses by using a J-A model;
secondly, acquiring a hysteresis loop I under different stresses according to the relationship between the external magnetic field strength and the magnetization strength calculated in the first step;
thirdly, intercepting a pipeline sample to be tested, and testing a hysteresis loop II of the intercepted pipeline sample to be tested in a stress-free state through a hysteresis loop test;
and fourthly, approximating the obtained hysteresis loop I and the hysteresis loop II by adopting a particle swarm optimization to obtain a J-A model parameter when the mean square error of data on the two curves is smaller than a set value or the minimum value, wherein the parameter is a material force magnetic characteristic parameter.
Example 2: as shown in fig. 3, as an optimization of the foregoing embodiment, in the fourth step, the method of approximation by using a particle swarm algorithm is as follows: and approximating the calculated data of the J-A model with the experimental data acquired by the hysteresis loop test, solving the mean square error of the calculated data and the experimental data, and outputting the force-magnetic characteristic parameters of the J-A model when the mean square error is smaller than a set value or the mean square error is minimum.
Example 3: as shown in fig. 3, as the optimization of the above embodiment 2, when the mean square error is not less than the set value or does not reach the minimum value, the particle swarm algorithm is continuously used for approximation until the mean square error is less than the set value or reaches the minimum value or the number of times of approximation calculation reaches the set value of the number of times of calculation.
Example 4: and a fifth step of substituting the parameters obtained in the fourth step into the J-A model to determine the relationship between different stresses and the hysteresis loop of the material so as to identify the stress in strong and weak magnetic detection.
Example 5: as shown in fig. 2 to 3, the method for determining the material force magnetic property parameter for strong and weak magnetic detection includes: firstly, setting initial parameters of a J-A model, calling a J-A model calculation subprogram, namely calculating the relationship between the magnetic field intensity and the magnetization intensity according to a calculation formula of the J-A model, and drawing a J-A model theoretical hysteresis loop I according to the relationship between the magnetic field intensity and the magnetization intensity, wherein the calculation formula is as follows:
He=H+αM+Hσ （1）
h is the intensity of the external magnetic field, alpha is the coupling coefficient inside the magnetic domain, and H sigma is the change of the equivalent field influenced by the stress;
Hσ=3σ/μ0[(r(1(0))+r(1(0))^'σ)M+2(r(2(0))+r(2(0))^'σ)M^3] （2）
wherein r (1) (0), r (2) (0) are all fixed constants, sigma is stress, mu 0 is vacuum permeability, and M is magnetization; substituting (2) into (1) to obtain the total equivalent field He;
Man=Ms[coth(He/a)-a/He] （3）
wherein, Ms is the saturation magnetization of the material, is related to the property of the material, and is usually obtained through experiments, and the value is 1.585 × 10^ 6; a is a magnetization curve shape coefficient;
dM/dH=(-μ0/kδ(Man-M)-c/(1-c)(dMan)/dH)/(μ0/kδ(Man-M){α+3σ/μ0[(r1(0)+r1(0)^'σ)+ 6(r2(0) +r2(0)^' σ) M^2 ]}-1/(1-c)) （4）
substituting the formulas (1), (2) and (3) into the formula (4) to obtain the relation between M and H, and drawing a hysteresis loop under stress-free conditions by using the relation; wherein k is the pinning coefficient; δ is related to the magnetization direction, and is equal to 1 in the forward magnetization direction and equal to-1 in the reverse magnetization direction, and c is the reversible coefficient.
And performing hysteresis loop test on the pipeline to be tested to obtain a hysteresis loop II of the stress-free state sample, then approximating the calculated data of the J-A model with the experimental data acquired by the hysteresis loop test by adopting a particle swarm algorithm, solving the mean square error of the calculated data and the experimental data, outputting the force-magnetic characteristic parameters of the J-A model when the mean square error is less than a set value, and continuing approximating by adopting the particle swarm algorithm when the mean square error is not less than the set value until the mean square error is less than the set value or the approximation calculation times reach the set value of the calculation times.
Substituting the obtained force magnetic characteristic parameters into a J-A model to determine the relation between different stresses and material hysteresis loops, acquiring magnetic induction intensity data in the process of testing the hysteresis loops of the pipeline to be tested, and filtering the acquired magnetic induction intensity data, wherein the filtering method comprises the following steps: determining the maximum deviation value A allowed by two times of sampling, and judging when a new value is detected each time: if the difference between the current value and the previous value is greater than A, the current value is invalid, the current value is abandoned, the previous value is used for replacing the current value, and interference signals are filtered; if the difference between the current value and the previous value is less than or equal to A, the current value is valid. And taking the magnetic induction intensity result obtained by filtering as final experimental data.
And (3) hysteresis loop test: the induction coil collects the magnetic induction intensity of the material under different external magnetic field intensities, and then a hysteresis loop is drawn according to the obtained data.
As shown in fig. 4, the results indicate that the stress causes the magnetization curve to shift downward. Under the condition of weak magnetism, the difference value of the magnetization curves with stress and without stress is larger, and under the condition of strong magnetism, the difference value of the magnetization curves with stress and without stress is smaller, so that the weak magnetism can effectively identify the stress. The conclusion provides a theoretical basis for strong and weak magnetic detection.
As shown in fig. 5, in the weak magnetic condition, the difference between the stressed and unstressed hysteresis loops is large, in the strong magnetic condition, the difference between the stressed and unstressed hysteresis loops is small, and the stress and the hysteresis loops have a corresponding relationship, and the stress applied to the material can be determined by using the relationship.
In summary, the method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection of the present invention can determine the force magnetic characteristic parameters of the material in strong and weak magnetic detection, and the force magnetic characteristic parameters calculated by the method can be used in the J-a model, so that the accurate hysteresis loops of the material under different stresses can be determined, and the stress in strong and weak magnetic detection can be identified by using the relationship between the stress and the hysteresis loops, so that the method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection of the present invention has a very wide engineering application prospect.
The technical characteristics form an embodiment of the invention, which has strong adaptability and implementation effect, and unnecessary technical characteristics can be increased or decreased according to actual needs to meet the requirements of different situations.
Claims (4)
1. A method for determining the magnetic characteristic parameters of a material force for strong and weak magnetic detection is characterized by comprising the following steps:
firstly, calculating the relationship between the magnetization intensity of a pipeline sample to be measured and the intensity of an external magnetic field under different stresses by using a J-A model;
secondly, acquiring a hysteresis loop I under different stresses according to the relationship between the external magnetic field strength and the magnetization strength calculated in the first step;
thirdly, intercepting a pipeline sample to be tested, and testing a hysteresis loop II of the intercepted pipeline sample to be tested in a stress-free state through a hysteresis loop test;
and fourthly, approximating the obtained hysteresis loop I and the hysteresis loop II by adopting a particle swarm optimization, and obtaining a J-A model parameter which is the material force magnetic characteristic parameter when the mean square error of the data on the two curves is smaller than a set value or the minimum value.
2. The method for determining the material force magnetic characteristic parameters for strong and weak magnetic detection according to claim 1, wherein in the fourth step, the particle swarm optimization approach is adopted as follows: and approximating the calculated data of the J-A model with the experimental data acquired by the hysteresis loop test, solving the mean square error of the calculated data and the experimental data, and outputting the force-magnetic characteristic parameters of the J-A model when the mean square error is smaller than a set value or the mean square error is minimum.
3. The method for determining the parameters of the material force and magnetic properties for strong and weak magnetic detection as claimed in claim 2, wherein when the mean square error is not less than the set value or does not reach the minimum value, the particle swarm optimization is continuously used for approximation until the mean square error is less than the set value or reaches the minimum value or the number of times of approximation calculation reaches the set value of the number of times of calculation.
4. The method for determining the parameters of the magnetic properties of the material force for strong and weak magnetism detection according to claim 1, 2 or 3, further comprising a fifth step of substituting the parameters obtained in the fourth step into the J-A model to determine the hysteresis loop relations between different stresses and the material so as to identify the stresses in the strong and weak magnetism detection.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116702564A (en) * | 2023-07-14 | 2023-09-05 | 西南石油大学 | Self-leakage magnetic field calculation method considering pipeline characteristics |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101246143A (en) * | 2008-04-02 | 2008-08-20 | 吉林大学 | Device for measuring ferromagnetic material internal stress by impulse electromagnetic field |
| CN201173910Y (en) * | 2008-04-02 | 2008-12-31 | 吉林大学 | Device for utilizing pulse electromagnetic field for measuring ferromagnetic material inner stress |
| CN102480260A (en) * | 2011-09-23 | 2012-05-30 | 浙江吉利汽车研究院有限公司 | Position signal interference processing method in permanent magnet synchronous motor rotor angle measuring device |
| CN108519569A (en) * | 2018-05-07 | 2018-09-11 | 上海交通大学 | JA hysteresis model parameter identification methods containing stress |
| CN110787340A (en) * | 2019-11-08 | 2020-02-14 | 湖南长城医疗科技有限公司 | Method and device for detecting dropping speed of infusion |
| CN112903162A (en) * | 2021-01-20 | 2021-06-04 | 中国石油大学(华东) | Method for evaluating residual stress distribution characteristics of natural gas pipeline circumferential weld by using coercive force |
-
2021
- 2021-11-10 CN CN202111328588.XA patent/CN114114103A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101246143A (en) * | 2008-04-02 | 2008-08-20 | 吉林大学 | Device for measuring ferromagnetic material internal stress by impulse electromagnetic field |
| CN201173910Y (en) * | 2008-04-02 | 2008-12-31 | 吉林大学 | Device for utilizing pulse electromagnetic field for measuring ferromagnetic material inner stress |
| CN102480260A (en) * | 2011-09-23 | 2012-05-30 | 浙江吉利汽车研究院有限公司 | Position signal interference processing method in permanent magnet synchronous motor rotor angle measuring device |
| CN108519569A (en) * | 2018-05-07 | 2018-09-11 | 上海交通大学 | JA hysteresis model parameter identification methods containing stress |
| CN110787340A (en) * | 2019-11-08 | 2020-02-14 | 湖南长城医疗科技有限公司 | Method and device for detecting dropping speed of infusion |
| CN112903162A (en) * | 2021-01-20 | 2021-06-04 | 中国石油大学(华东) | Method for evaluating residual stress distribution characteristics of natural gas pipeline circumferential weld by using coercive force |
Non-Patent Citations (3)
| Title |
|---|
| 朱欣华: "《智能仪器原理与设计》", 中国计量出版社, pages: 106 - 107 * |
| 李伊玲等: "机械应力作用下电工钢片静态磁滞特性模拟方法研究", 《中国电力》, vol. 53, no. 10, pages 10 * |
| 王洋等: "基于蛙跳模糊算法的Jiles Atherton 铁心磁滞模型参数确定", 《电工技术学报》, vol. 32, no. 4, pages 154 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116702564A (en) * | 2023-07-14 | 2023-09-05 | 西南石油大学 | Self-leakage magnetic field calculation method considering pipeline characteristics |
| CN116702564B (en) * | 2023-07-14 | 2023-09-29 | 西南石油大学 | Self-leakage magnetic field calculation method considering pipeline characteristics |
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