CN100356169C - Quantizing method for detecting corrosion defect by magnetic leakage - Google Patents
Quantizing method for detecting corrosion defect by magnetic leakage Download PDFInfo
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- CN100356169C CN100356169C CNB2005100111166A CN200510011116A CN100356169C CN 100356169 C CN100356169 C CN 100356169C CN B2005100111166 A CNB2005100111166 A CN B2005100111166A CN 200510011116 A CN200510011116 A CN 200510011116A CN 100356169 C CN100356169 C CN 100356169C
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Abstract
The present invention relates to a quantizing method for detecting corrosion defects by magnetic leakage, and belongs to the technical field of the detection without damage. The present invention utilizes the distribution characteristic of a detected leakage magnetic field to quantize the dimension of the corrosion defects according to a specific algorithm. The present invention has the concrete implementation method that firstly, a sample with three series of standard defects is manufactured; according to the magnetic leakage detection data of the sample, the coefficients in a length quantizing formula, a width quantizing formula and a depth quantizing formula of the corrosion defects are determined; the method for quantizing corrosion defects of the detected member of the sample with the type is obtained, which provides bases for the evaluation of use states of devices and the device maintenance. The present invention effectively overcomes the disadvantage that the prior art is difficult to quantize the corrosion defects, particularly the defect depth. The method is simple and easy to implement. The method can be realized by manual work and computers, the efficiency is high, and the method has wide application prospects.
Description
Technical field
The present invention relates to a kind of corrosion default Magnetic Flux Leakage Inspecting data analysis processing method, relate in particular to the quantization method of detecting corrosion defect by magnetic leakage, belong to technical field of nondestructive testing.
Background technology
Magnetic Flux Leakage Inspecting is a nondestructiving detecting means commonly used, in pressure vessel, pressure pipeline and other security fields important application is arranged, and still, for a long time, how to utilize the Magnetic Flux Leakage Inspecting data to judge the flaw size of detected parts, is a difficult problem always.Usually adopt manual analysis Magnetic Flux Leakage Inspecting data to judge the method for defective, often by means of experience, efficient is lower, and is difficult to quantize.
That Chinese patent literature discloses is a kind of " pipeline defect and magnetic leakage detects the analytical approachs of data " (publication number: 1458442, open day: 2003.11.26), this technology relates to a kind of pipeline defect and magnetic leakage that can improve various steel pipe defect detection signal analysis efficiencies and accuracy of quantitative analysis and detects data analysis processing method, by the video data cloud atlas, judge whether defectiveness of pipeline, but there is the shortcoming of quantification difficult in this technology, particularly is difficult to quantize the degree of depth of corrosion default.
Summary of the invention
The quantization method that the purpose of this invention is to provide a kind of detecting corrosion defect by magnetic leakage, this method is utilized detected stray field distribution characteristics, realize quantification according to simple algorithm, for valuator device user mode and plant maintenance provide foundation to three direction sizes of corrosion default.
A kind of quantization method of detecting corrosion defect by magnetic leakage is characterized in that this method comprises the steps:
1) get the sample of identical material with parts to be detected, same thickness, sample thickness is represented with symbol t; Processing length is respectively 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t thereon, and width is 3t, and the degree of depth is 20%t; Length is 3t, and width is respectively 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t, the degree of depth is 20%t; Length and width are 3t, and three series that the degree of depth is respectively 10%t, 20%t, 30%t, 40%t, 50%t, 60%t, 70%t, 80%t and 90%t are manually corroded drawbacks of the standard, and defective border arc transition is at least 20t at interval between the defective;
2) with the sample horizontal positioned, with dc magnetization field saturated magnetization, equidistantly sampling in lift-off value is the detection plane of 0.5～5mm then, the discrete two-dimensional stray field that obtains detection plane internal standard defect level direction distributes, and described lift-off value is meant the distance of detection probe apart from detected specimen surface;
3) with step 2) the discrete two-dimensional stray field data that obtain average, 1.2 times that use this mean value again as threshold filtering step 2) the discrete two-dimensional stray field data that obtain, obtain the discrete two-dimensional stray field data area of each drawbacks of the standard;
4) difference calculation procedure 3) length, width and the peak value of the drawbacks of the standard discrete two-dimensional stray field that obtains; The sampling number that the discrete stray field length L m of drawbacks of the standard equals drawbacks of the standard discrete two-dimensional stray field length direction multiply by sampling interval d; The sampling number that defect magnetic flux leakage field width W m equals defective discrete two-dimensional stray field Width multiply by sampling interval d; Defect magnetic flux leakage field peak value Mx is a defective discrete two-dimensional stray field maximal value;
5) the defective width that step 4) is obtained is that 3t, the degree of depth are that 20%t, length are respectively its corresponding defect length L of drawbacks of the standard stray field length L m of 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t by the linear formula match, determine coefficient a and b among defect length computing formula L=a * Lm+b, obtain the defect length quantitative formula; The defect length that step 4) is obtained is that 3t, the degree of depth are that 20%t, width are respectively its corresponding defective width W of drawbacks of the standard stray field width W m of 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t by the linear formula match, determine that the defective width quantizes coefficient e and the f among formula W=e * Wm+f, obtains defective width quantitative formula; Defect length that step 4) is obtained and width all be 3t, the degree of depth be respectively 10%t, 20%t, 30%t, 40%t, 50%t, 60%t, 70%t, 80%t and 90%t its corresponding depth of defect D of drawbacks of the standard stray field peak value Mx by the quadratic formula match, determine depth of defect quantitative formula Mx=g * D
2Coefficient g, h and j among+h * D+j obtain the depth of defect quantitative formula;
6) detected parts are used dc magnetization field saturated magnetization, with step 2) in lift-off value and the sampling interval discrete stray field data that obtain unit under test, set by step 3) obtain the discrete two-dimensional stray field data of each defective of measured piece, set by step 4) obtain length, width and the peak value of each defect magnetic flux leakage field of measured piece, set by step 5) defect length quantitative formula, defective width quantitative formula and depth of defect quantitative formula promptly calculate the size of the unknown corrosion default of detected parts.
In said method of the present invention, described step 2) spacing of intermediate reach sampling is 0.1～10mm.
The present invention utilizes detected stray field distribution characteristics, can realize quantification exactly according to simple algorithm to three direction sizes of component corrosion defective to be measured, effectively overcome in the prior art corrosion default, particularly the shortcoming that depth of defect is difficult to quantize; Method is simple, and manual and computing machine can realize that all the efficient height has more wide application prospect.
Description of drawings
Fig. 1 is the data point that obtains of test experience and the fitting a straight line of defect length L and defect magnetic flux leakage field length L m.
Fig. 2 is the data point that obtains of test experience and the fitting a straight line of defective width W and defect magnetic flux leakage field width W m.
Fig. 3 is the data point that obtains of test experience and the matched curve of depth of defect D and defect magnetic flux leakage field peak value Mx.
Embodiment
Can further understand content of the present invention below by specific embodiment.
Use circumferentially evenly the distribute pipe leakage detector MT1 of 300 detection probe of a kind of edge that the pipe under test of bore 273mm, wall thickness 10mm is detected, each probe of detecting device is 2.86mm at the pipeline axial sampling interval, the sampling interval of circumferentially respectively popping one's head in along pipeline is 2.86mm, and detection probe is 3mm apart from the distance of detected specimen surface.
Before pipeline corrosion default is detected, advanced column criterion defects detection experiment.Promptly get a bore and be 273mm, wall thickness and be 10mm and with pipe to be detected standard pipe with material, processing length is respectively 10mm, 20mm, 30mm, 40mm, 50mm, 60mm, 70mm, 80mm, 90mm and 100mm thereon, width is 30mm, and the degree of depth is 2mm; Length is 30mm, and width is respectively 10mm, 20mm, 30mm, 40mm, 50mm, 60mm, 70mm, 80mm, 90mm and 100mm, and the degree of depth is 2mm; Length and width all are 30mm, and the degree of depth is respectively 3 artificial corrosion defaults of series of 1mm, 2mm, 3mm, 4mm, 5mm, 6mm, 7mm, 8mm and 9mm, and defective border arc transition equals 200mm at interval between the defective.Sample by axial, circumferential with pipe leakage detector MT1 then, spacing is all carried out defects detection for 2.86mm, lift-off value is 3mm, obtain the discrete two-dimensional stray field data of detection plane internal standard defect level direction, this detection data mean value is 125 Gausses (Gauss), get 1.2 * 125=150 and detect data, obtain the stray field distribution discrete data of each drawbacks of the standard as threshold filtering.
Calculate the stray field length of each drawbacks of the standard: the sampling number that the stray field length L m of drawbacks of the standard equals drawbacks of the standard discrete two-dimensional stray field length direction multiply by sampling interval 2.86mm.It is that 30mm, the degree of depth are that the length L of its corresponding drawbacks of the standard of stray field length L m of drawbacks of the standard of 2mm is by the linear formula match that length is respectively 10mm, 20mm, 30mm, 40mm, 50mm, 60mm, 70mm, 80mm, 90mm and 100mm, width, obtain defect length computing formula (formula one) L=1.01Lm+1.84, Fig. 1 is the straight line that fits of the data point that obtains of drawbacks of the standard test experience and defect length L and defect magnetic flux leakage field length L m.
Calculate the stray field width of each drawbacks of the standard: the sampling number that the stray field width W m of drawbacks of the standard equals drawbacks of the standard discrete two-dimensional stray field Width multiply by sampling interval 2.86mm.With the degree of depth is 2mm, length is that its corresponding drawbacks of the standard width W of stray field width W m of 30mm, the width drawbacks of the standard that is respectively 10mm, 20mm, 30mm, 40mm, 50mm, 60mm, 70mm, 80mm, 90mm and 100mm is by the linear formula match, obtain defective width computing formula (formula two) W=1.28Wm-12, Fig. 2 is the straight line that fits of the data point that obtains of drawbacks of the standard test experience and defective width W and defect magnetic flux leakage field width W m.
Calculate the stray field peak value of each drawbacks of the standard: drawbacks of the standard stray field peak value Mx is a drawbacks of the standard discrete two-dimensional stray field maximal value.With length and width all be its corresponding drawbacks of the standard depth D of stray field peak value Mx of 30mm, the degree of depth drawbacks of the standard that is respectively 1mm, 2mm, 3mm, 4mm, 5mm, 6mm, 7mm, 8mm and 9mm by the quadratic formula match, obtain depth of defect computing formula (formula three) Mx=0.28D
2+ 7.68D+208.72, Fig. 3 are the curves that fits of the data point that obtains of drawbacks of the standard test experience and depth of defect D and defect magnetic flux leakage field peak value Mx.
Then, with pipe leakage detector MT1 to bore 273mm, corrosion default on the pipe under test of wall thickness 10mm detects, testing conditions is identical with above-mentioned drawbacks of the standard experiment, the stray field data mean value that detection obtains is 120 Gausses, therefore, fetching data and filtering threshold value is 1.2 * 120=144, filter and detect data, obtained a defect magnetic flux leakage field, its stray field length is 53mm, the stray field width is 86mm, the stray field peak value is 255.4 Gausses, by above-mentioned quantifying defects formula (formula one, formula two, formula three) obtains the length of defective, wide, be respectively 55.37mm deeply, 110mm, 4.7mm.This defective of actual measurement, is respectively 55mm, 100mm, 5mm deeply at its length and width, and the quantifying defects error is less than 10%.
Find that by a large amount of test experience can effectively quantize various corrosion defaults with the inventive method, quantization error is less than 10%, and algorithm of the present invention is simple, be fit to the efficient occasion that a large amount of detection data are arranged of handling.
Claims (1)
1. the quantization method of a detecting corrosion defect by magnetic leakage is characterized in that this method comprises the steps:
1) get the sample of identical material with parts to be detected, same thickness, sample thickness is represented with symbol t; Processing length is respectively 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t thereon, and width is 3t, and the degree of depth is 20%t; Length is 3t, and width is respectively 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t, the degree of depth is 20%t; Length and width are 3t, and three series that the degree of depth is respectively 10%t, 20%t, 30%t, 40%t, 50%t, 60%t, 70%t, 80%t and 90%t are manually corroded drawbacks of the standard, and defective border arc transition is at least 20t at interval between the defective;
2) with the sample horizontal positioned, with dc magnetization field saturated magnetization, equidistantly sampling in lift-off value is the detection plane of 0.5～5mm then obtains the discrete two-dimensional stray field data of detection plane internal standard defect level direction; Described lift-off value is meant the distance of detection probe apart from detected specimen surface;
3) with step 2) the discrete two-dimensional stray field data that obtain average, 1.2 times that use this mean value again as threshold filtering step 2) the discrete two-dimensional stray field data that obtain, obtain the discrete two-dimensional stray field data area of each drawbacks of the standard;
4) difference calculation procedure 3) length, width and the peak value of the drawbacks of the standard discrete two-dimensional stray field that obtains; The sampling number that the discrete stray field length L m of drawbacks of the standard equals drawbacks of the standard discrete two-dimensional stray field length direction multiply by sampling interval d; The sampling number that defect magnetic flux leakage field width W m equals defective discrete two-dimensional stray field Width multiply by sampling interval d; Defect magnetic flux leakage field peak value Mx is a defective discrete two-dimensional stray field maximal value;
5) the defective width that step 4) is obtained is that 3t, the degree of depth are that 20%t, length are respectively its corresponding defect length L of drawbacks of the standard stray field length L m of 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t by the linear formula match, determine coefficient a and b among defect length computing formula L=a * Lm+b, obtain the defect length quantitative formula; The defect length that step 4) is obtained is that 3t, the degree of depth are that 20%t, width are respectively its corresponding defective width W of drawbacks of the standard stray field width W m of 1t, 2t, 3t, 4t, 5t, 6t, 7t, 8t, 9t and 10t by the linear formula match, determine that the defective width quantizes coefficient e and the f among formula W=e * Wm+f, obtains defective width quantitative formula; Defect length that step 4) is obtained and width all be 3t, the degree of depth be respectively 10%t, 20%t, 30%t, 40%t, 50%t, 60%t, 70%t, 80%t and 90%t its corresponding depth of defect D of drawbacks of the standard stray field peak value Mx by the quadratic formula match, determine depth of defect quantitative formula Mx=g * D
2Coefficient g, h and j among+h * D+j obtain the depth of defect quantitative formula;
6) detected parts are used dc magnetization field saturated magnetization, with step 2) in lift-off value and the sampling interval discrete two-dimensional stray field data that obtain unit under test, set by step 3) obtain the discrete two-dimensional stray field data of each defective of measured piece, set by step 4) obtain length, width and the peak value of each defect magnetic flux leakage field of measured piece, set by step 5) defect length quantitative formula, defective width quantitative formula and depth of defect quantitative formula promptly calculate the size of the unknown corrosion default of detected parts.
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Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN100427947C (en) * | 2006-06-16 | 2008-10-22 | 清华大学 | Large-area steel plate defect flux-leakage detection method |
| CA2792268C (en) * | 2010-03-10 | 2018-09-18 | Jrb Engineering Pty Ltd | Method and apparatus for magnetic crack depth prediction |
| CN102095793B (en) * | 2011-01-04 | 2012-08-29 | 台州市特种设备监督检验中心 | Quantitative magnetic flux leakage testing method for defect at root part of butt weld of pipeline |
| CN104458895A (en) * | 2014-12-08 | 2015-03-25 | 清华大学 | Three-dimensional pipeline leakage flux imaging detection method and system |
| CN104458896B (en) * | 2014-12-10 | 2017-07-18 | 华中科技大学 | A kind of flaw evaluation method based on multiple Analysis of Magnetic Flux Leakage Testing Signals characteristic value |
| CN104514987B (en) * | 2014-12-19 | 2017-02-22 | 清华大学 | Three-dimensional pipeline flux leakage imaging defect quantizing method |
| CN106198368B (en) * | 2016-06-30 | 2018-09-21 | 重庆交通大学 | Inside concrete steel bar corrosion method for detecting position |
| CN106290551A (en) * | 2016-10-11 | 2017-01-04 | 武汉华宇目检测装备有限公司 | The multiple dimensioned leakage field accurate detecting method of a kind of pipe corrosion and device |
| CN106770627B (en) * | 2016-12-16 | 2019-12-13 | 北京华航无线电测量研究所 | Axial magnetic flux leakage signal length quantization method |
| CN106814131B (en) * | 2016-12-30 | 2020-05-29 | 哈尔滨工业大学深圳研究生院 | Ferromagnetic planar member shallow layer damage magnetic emission detection method and magnetic emission detection system |
| CN107817290B (en) * | 2017-10-19 | 2020-04-07 | 清华大学 | Defect magnetic flux leakage signal solving method based on depth-lift-off value transformation |
| CN111337566B (en) * | 2020-02-25 | 2021-10-22 | 清华大学 | Method for identifying defect edge in magnetic flux leakage detection |
| CN111999377B (en) * | 2020-08-31 | 2023-04-07 | 河北工业大学 | Method for characterizing defect width through magnetic flux leakage detection |
| CN112179977A (en) * | 2020-09-28 | 2021-01-05 | 广东省特种设备检测研究院茂名检测院 | Surface morphology measuring and deducting method in pipeline weld flux leakage detection |
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| CN1458442A (en) * | 2003-05-14 | 2003-11-26 | 天津大学 | Analysing method for detection data of pipeline defect leaking magnet |
| JP2008025893A (en) * | 2006-07-20 | 2008-02-07 | Jfe Engineering Kk | Moving device in boiler water tube group |
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| CN1458442A (en) * | 2003-05-14 | 2003-11-26 | 天津大学 | Analysing method for detection data of pipeline defect leaking magnet |
| JP2008025893A (en) * | 2006-07-20 | 2008-02-07 | Jfe Engineering Kk | Moving device in boiler water tube group |
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