A polyurethane heat preservation pipe medium layer defect comparison method based on spacing effect and application

Abstract

The application discloses a polyurethane heat preservation pipe medium layer defect comparison method based on a pitch effect and application, and comprises the following steps: receiving input different pitch capacitance imaging detection signals, calculating the absolute value of defect signal change, and judging whether it is greater than or equal to a preset threshold; if not, the defect does not exist; if yes, the defect exists; when the defect exists, the distortion rate of the detection signal is calculated, the distortion rate value at the defect center is extracted, and a distortion rate curve cluster diagram is drawn; whether the curve has monotonicity or concave-convexity is judged; if not, it does not belong to a single layer defect; if yes, whether the distortion rate is less than 0 is judged; if yes, the curve is a protective layer defect, the larger one on the left side of the intersection curve is a heat preservation layer defect, and the smaller one is a working tube defect; if not, classification is carried out according to whether the curve intersects; the non-intersection is a heat preservation layer defect; the larger one on the left side of the intersection curve is a protective layer defect, and the smaller one is a working tube defect. The application can simultaneously avoid the interference of noise signals and mixed medium layer defects on the distinction of three kinds of medium layer defects.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nondestructive testing signal processing, and in particular to a polyurethane thermal insulation pipe medium layer defect comparison method based on spacing effect and application. BACKGROUND

[0002] At present, polyurethane thermal insulation pipes are widely used in the transportation of hot oil, heating and cooling and the thermal insulation and cooling engineering of petroleum, chemical industry, coal mine, warm room and cold storage industry, and play an important role in related application fields. The polyurethane thermal insulation pipe is composed of a working steel pipe (working pipe), hard polyurethane foam plastic (thermal insulation layer) and high-density polyethylene sleeve pipe (protective layer). In the production, transportation, installation and operation process of the polyurethane thermal insulation pipe, defects may exist in the working pipe, the thermal insulation layer and the protective layer. The above defects will affect the safety of the application field of the polyurethane thermal insulation pipe and cause safety hazards and safety accidents. Due to the particularity of the medium transported by the polyurethane thermal insulation pipe, compared with the safety accidents of conventional pipelines, the polyurethane thermal insulation pipe will cause more serious personnel casualties and property losses. Comparing and distinguishing the defects of the working pipe, the thermal insulation layer and the protective layer in the polyurethane thermal insulation pipe is helpful to take reasonable maintenance scheme and eliminate safety hazards as soon as possible, which is of great significance to ensure the safety of the application field of the polyurethane thermal insulation pipe.

[0003] The capacitive imaging detection technology is a new type of nondestructive testing technology, which can effectively detect defects of insulating materials and defects of metal materials. The spacing effect of the capacitive imaging detection technology refers to that when the capacitive sensor based on the capacitive imaging detection technology has different electrode spacings, the capacitive sensor can detect the physical characteristics of the measured object at different depths. In the three medium layers of the polyurethane thermal insulation pipe, the protective layer and the thermal insulation layer are insulating materials, and the working pipe is a metal material. At present, the capacitive imaging detection technology can only detect the defects of the protective layer, the thermal insulation layer and the working pipe in the polyurethane thermal insulation pipe, and cannot distinguish the defects of the three medium layers of the polyurethane thermal insulation pipe.

[0004] Therefore, it is necessary to propose a distinguishing method which can be applied to the defects of the protective layer, the thermal insulation layer and the working pipe in the polyurethane thermal insulation pipe. SUMMARY

[0005] In order to overcome the above problems in the prior art, the present application provides a polyurethane thermal insulation pipe medium layer defect comparison method based on spacing effect and application.

[0006] The technical scheme adopted by the present application to solve its technical problems is: a polyurethane thermal insulation pipe medium layer defect comparison method based on spacing effect, comprising the following steps:

[0007] Step 1, receiving input capacitive imaging detection signals under different electrode spacings;

[0008] Step 2, calculate the absolute value of the defect signal change |△Y of the capacitive imaging detection signal obtained in step 1 n , and determine whether |△Y n is greater than or equal to a preset threshold P n ; if not, it is determined that there is no defect, and if yes, it is determined that there is a defect;

[0009] Step 3, after determining that there is a defect, calculate the distortion rate RY n of the capacitive imaging detection signal obtained in step 1 n , extract RY n at the center of the defect, and draw a RY n curve cluster graph at the same starting point;

[0010] Step 4, determine whether the RY n curve cluster has monotonicity or concave-convexity; if not, it is determined that it does not belong to a single medium layer defect; if yes, proceed to the next step;

[0011] Step 5, determine whether there is a RY n curve less than 0 in the RY n curve cluster; if yes, the RY n curve is determined to be a polyurethane insulation pipe protective layer defect, the RY n curve with a larger value on the left side of the intersection point is determined to be a polyurethane insulation pipe insulation layer defect, and the RY n curve with a smaller value is determined to be a polyurethane insulation pipe working tube defect; if not, proceed to the next step;

[0012] Step 6, classify the RY n curve cluster according to whether the RY n curves intersect; the RY n curve that does not intersect is a polyurethane insulation pipe insulation layer defect; the RY n curve with a larger value on the left side of each intersection point is a polyurethane insulation pipe protective layer defect, and the RY n curve with a smaller value is a polyurethane insulation pipe working tube curve.

[0013] The above-mentioned polyurethane insulation pipe medium layer defect comparison method based on the spacing effect, the capacitive imaging detection signal under different electrode spacings in step 1 includes a limited number of capacitive sensor detection signals Y n of polyurethane insulation pipes containing three kinds of medium layer defects under continuously increasing electrode spacings and capacitive sensor detection signals YS n of defect-free polyurethane insulation pipes under different electrode spacings.

[0014] The above-mentioned method for comparing defects in the medium layer of polyurethane insulation pipes based on the spacing effect, wherein in step 2, the absolute value of the defect signal change |ΔY n |=|Y n -YS n |

[0015] The above-mentioned method for comparing defects in the medium layer of polyurethane insulation pipes based on the spacing effect, wherein the preset threshold P in step 2... n YS is a detection signal of a defect-free polyurethane insulation pipe detected by a capacitive sensor with different electrode spacing. n Set the preset threshold P n .

[0016] The above-mentioned method for comparing defects in the dielectric layer of polyurethane insulation pipes based on the spacing effect, wherein the distortion rate RY in step 3... n =(Y n -YS n ) / YS n RY at the center of the defect n The RY represents the maximum or minimum value of the distortion rate. n The curve cluster diagram is formed by discrete defect centers RY. n The values ​​are fitted together.

[0017] The above-mentioned method for comparing defects in the medium layer of polyurethane insulation pipes based on the spacing effect, wherein in step 2, the absolute value of the defect signal change |ΔY n | The distortion rate RY in step 3 n In step 4, determine RY n Whether the curve family has monotonicity or concavity / convexity is determined simultaneously using Excel, LabVIEW, MathType, MATLAB, and Python software to ensure accuracy.

[0018] The above-mentioned method for comparing defects in the dielectric layer of polyurethane insulation pipes based on the spacing effect is applied to determine defects in polyurethane insulation pipes containing three types of dielectric layer defects under multiple electrode spacings.

[0019] The beneficial effects of this invention are as follows: Based on the spacing effect of capacitance imaging detection technology, capacitance sensors with different electrode spacings can detect physical features of the measured object at different depths. Therefore, by using the detection results of different electrode spacings and processing the data, the inherent laws of the distortion rate curves corresponding to the three types of dielectric layer defects are discovered, thereby realizing the comparison and differentiation of the three types of dielectric layer defects in polyurethane insulation pipes. The method provided by this invention can simultaneously avoid the interference of noise signals and mixed dielectric layer defects on the differentiation of the three types of dielectric layer defects. Attached Figure Description

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] Figure 1 This is a flowchart of the defect comparison method of the present invention;

[0022] Figure 2 This is a flowchart of the preset threshold setting process of the present invention;

[0023] Figure 3 This is a structural diagram of the polyurethane insulation pipe in Embodiment 1 of the present invention;

[0024] Figures 4 to 11 This is a cluster of distortion rate curves for detecting defects in three media layers of a polyurethane insulation pipe at eight different unknown lift-off heights in Embodiment 1 of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] like Figure 1 As shown, this invention discloses a method for comparing defects in the dielectric layer of polyurethane insulation pipes based on the spacing effect. This method can be applied to determine defects in polyurethane insulation pipes containing three types of dielectric layer defects under multiple electrode spacings. Specifically, it includes the following steps:

[0027] S101, Receives input capacitance imaging detection signals under different electrode spacings, wherein the capacitance imaging detection signals under different electrode spacings include a finite number of continuously increasing electrode spacings (d1) <d2<……<d n-1 <d n The capacitive sensor under the condition detects the detection signals (Y1, Y2, ..., Y...) of the polyurethane insulation pipe containing three dielectric layer defects. n-1 Y n ) and different electrode spacings (d1) <d2<……<d n-1 <d n The capacitance sensor under the condition detects the detection signals (YS1, YS2, ..., YS) of the defect-free polyurethane insulation pipe. n-1 YS n ).

[0028] Specifically, the signal and mathematical processing software receives input capacitance imaging detection signals at different electrode spacings, where the capacitance imaging detection signals are a finite number of continuously increasing electrode spacings (d1). <d2<……<d n-1 <d n The capacitive sensor under the condition detects the detection signals (Y1, Y2, ..., Y...) of the polyurethane insulation pipe containing three dielectric layer defects. n-1 Y n ) and different electrode spacings (d1) <d2<……<dn-1 <d n The capacitance sensor under the condition detects the detection signals (YS1, YS2, ..., YS) of the defect-free polyurethane insulation pipe. n-1 YS n ).

[0029] S102, calculate the absolute value of the defect signal change |ΔY| from the capacitance imaging detection signal. n |=|Y n -YS n |;

[0030] S103, Determine the absolute value of the defect signal change |△Y n Is it greater than or equal to the preset threshold P? n ;

[0031] S104, if not, then it is determined that the three types of dielectric layer defects do not exist;

[0032] S105, if so, then the defect is determined to exist.

[0033] Specifically, after receiving the detection signal, the signal or mathematical processing software calls a pre-programmed computer processing program to calculate the absolute value of the defect signal change |ΔY|. n |=|Y n -YS n |. Introduce a preset threshold P n The absolute value of the defect signal change |ΔY n |With preset threshold P n Comparison, greater than threshold P n The defect is indicated by a value less than the threshold P. n The defect is not represented. The preset threshold P is... n The determination is that the signal or mathematical processing software receives the detection signal YS from the capacitive sensor to detect the defect-free polyurethane insulation pipe. n The dynamic variation ratio is used to avoid noise signal interference and improve the accuracy of defect discrimination for the three dielectric layers. For example, P is used. n =|(6%~10%)YS n |, such as Figure 2 As shown, it includes: a01, which receives electrodes with different spacings d. n The detection signal YS of the capacitive sensor under the condition of detecting defect-free polyurethane insulation pipe. n a02, based on the detection signal YS n Obtain different electrode spacings d n The preset threshold P under dynamic conditions n .

[0034] Preferably, the absolute value of the defect signal change |ΔY| is calculated from the capacitance imaging detection signal. n |=|Yn -YS n |Calculate the absolute value of the defect signal change|ΔY from the capacitance imaging detection signal. n |=|Y n -YS n |Including using Excel software to calculate the absolute value of defect signal changes| △Y n | Using LabVIEW software to calculate the absolute value of defect signal changes| △Y n | Using MathType software to calculate the absolute value of defect signal changes| △Y n | Using MATLAB software to calculate the absolute value of the defect signal change| △Y n |Using Python software to calculate the absolute value of the defect signal change| △Y n |

[0035] S106, Calculate the distortion rate RY for capacitance imaging detection signals with different electrode spacings. n =(Y n -YS n ) / YS n Among them, different electrode spacings (d1) <d2<……<d n-1 <d n ) corresponding to different defect signal distortion rates (RY1, RY2, ..., RY) n-1 RY n );

[0036] S107, Extract RY at the defect center. n Values, and draw RY from the same starting point. n Curve cluster diagram, where RY is located at the center of the defect. n The value represents the maximum or minimum value of the corresponding defect distortion rate, with the same starting point representing the same working electrode spacing, RY. n The curve cluster diagram is formed by discrete defect centers RY. n The values ​​are fitted together.

[0037] Preferably, the distortion rate RY is calculated for capacitance imaging detection signals with different electrode spacings. n =(Y n -YS n ) / YS n Determine the distortion rate RY of capacitance imaging detection signals with different electrode spacings. n =(Y n -YS n ) / YS n This includes using Excel software to calculate the distortion rate (RY) of the detection signal. n Calculate the distortion rate RY of the detection signal using LabVIEW software. n MathType software is used to calculate the distortion rate (RY) of the detected signal. nMATLAB software for calculating the distortion rate RY of the detection signal n Using Python software to calculate the distortion rate RY of the detected signal n .

[0038] S108, determine RY n Does the curve cluster exhibit monotonicity or unevenness? S109, if no, it is determined that it does not belong to a single dielectric layer defect; if yes, proceed to the next step of judgment.

[0039] S110, determine RY n Does the curve family contain RY values ​​less than 0? n curve;

[0040] S111, if so, then determine this RY. n The curve represents a protective layer defect, and the rest are RY. n The curves with larger RY values ​​to the left of the intersection point n The curve represents a defect in the insulation layer, with smaller RY values. n The curve indicates a defect in the working tube; if not, proceed to the next step.

[0041] S112, according to RY n Do the curves intersect for RY? n Classify curve clusters;

[0042] S113, non-intersecting RY n The curve represents a defect in the insulation layer;

[0043] S114, the larger RY value on the left side of each intersection point n The curve represents a protective layer defect, with a smaller RY value. n The curve is the working pipe curve.

[0044] The present invention provides a method for comparing and distinguishing defects in three dielectric layers of polyurethane insulation pipes based on the spacing effect of capacitance imaging detection technology. After receiving capacitance imaging detection signals under different electrode spacings, the method acquires capacitance imaging detection signals under different electrode spacings, including a finite number of continuously increasing electrode spacings (d1). <d2<……<d n-1 <d n The capacitive sensor under the condition detects the detection signals (Y1, Y2, ..., Y...) of the polyurethane insulation pipe containing three dielectric layer defects. n-1 Y n ) and different electrode spacings (d1) <d2<……<d n-1 <d n The capacitance sensor under the condition detects the detection signals (YS1, YS2, ..., YS) of the defect-free polyurethane insulation pipe. n-1 YS nUsing signal and mathematical processing software, calculate the absolute value of the defect signal change |ΔY]. n |=|Y n -YS n | and determine the absolute value of the defect signal change|△Y n Is it greater than or equal to the preset threshold P? n If not, the three types of dielectric layer defects are determined to be absent; if yes, the defects are determined to exist, thus filtering the defect detection signal and preventing interference from noise signals. To prevent excessive differences in the amplitude of defect detection signals from different dielectric layers, the distortion rate RY of the capacitance imaging detection signals with different electrode spacings is calculated using signal and mathematical processing software. n =(Y n -YS n ) / YS n Among them, different electrode spacings (d1) <d2<……<d n-1 <d n ) corresponding to different defect signal distortion rates (RY1, RY2, ..., RY) n-1 RY n To display defects from different dielectric layers in the same image, the RY region at the defect center is extracted. n Values, and draw RY from the same starting point. n Curve cluster diagram, where RY is located at the center of the defect. n The value represents the maximum or minimum value of the corresponding defect distortion rate, with the same starting point representing the same working electrode spacing, RY. n The curve cluster diagram is formed by discrete defect centers RY. n The values ​​were fitted. To prevent defects in the mixed dielectric layer from interfering with this method, the RY was determined. n Does the curve cluster exhibit monotonicity or unevenness? If not, it is determined not to belong to a single dielectric layer defect; if so, proceed to the next step. Determine RY. n Does the curve family contain RY values ​​less than 0? n Curve; if so, then determine this RY. n The curve represents a protective layer defect, and the rest are RY. n The curves with larger RY values ​​to the left of the intersection point n The curve represents a defect in the insulation layer, with smaller RY values. n The curve indicates a defect in the working tube; if not, proceed to the next step. According to RY... n Do the curves intersect for RY? n Classify curve clusters; disjoint RY n The curve represents defects in the insulation layer; the larger RY value to the left of each intersection point. n The curve represents a protective layer defect, with a smaller RY value. nThe curve represents the working tube curve. The method provided by this invention can simultaneously avoid interference from noise signals and mixed dielectric layer defects in distinguishing between the three types of dielectric layer defects, by determining the RY... n Whether the curve family has monotonicity or concavity / convexity, and how to determine RY. n Does the curve family contain RY values ​​less than 0? n Curve, according to RY n Do the curves intersect for RY? n The process involves steps such as classifying curve clusters to differentiate and contrast defects in the three media layers of polyurethane insulation pipes.

[0045] Based on the above differentiation method, the electrode spacing d is given in Example 1. n The experimental implementation method for specific numerical values ​​is used to verify the effectiveness of the method.

[0046]

Example 1

[0047] A schematic diagram of the polyurethane insulation pipe test specimen is shown below. Figure 3 As shown, the polyurethane insulated pipe consists of a protective layer, an insulation layer, and a working pipe. These three media layers are made of three different materials: high-density polyethylene, rigid polyurethane foam, and steel, respectively. Each media layer contains one defect. The electrode spacing d... n Capacitive sensors with diameters of 2mm, 2.5mm, 3mm, 3.5mm, 4mm, 4.5mm, 5mm, 5.5mm, and 6mm were used to detect defects in the protective layer, insulation layer, and working pipe of polyurethane insulation pipes. In addition, to avoid the influence of lift-off height during capacitive imaging detection on the method of this invention, eight unknown lift-off heights were used to detect the polyurethane insulation pipes in the experiment. The absolute value of the defect signal change |ΔY| was calculated for each of the acquired detection results. n |=|Y n -YS n | Find the distortion rate RY n =(Y n -YS n ) / YS n Extract the defect center RY n And plot the distortion rate curve clusters from the same starting point, the eight curve clusters are as follows: Figures 4 to 11 As shown. Figure 4 For example, Figure 4 The three fitted curves exhibit monotonicity or concavity / convexity, indicating the presence of three types of dielectric layer defects according to this invention; further, it is determined whether there is a distortion rate curve less than 0 in the distortion rate curve cluster diagram, from... Figure 4It can be seen that the number I distortion rate curve exists less than 0 case, thus judging that the number I defect is the protective layer defect, and the other two curves are on the left side of the intersection point, the number II curve has a larger value, and the number III curve has a smaller value, that is, the number II curve is the insulation layer defect, and the number III is the working tube defect, and the above three medium layer defect comparison results are completely consistent with the icon. For example, Figure 11 Figure 11 The three fitting curves present monotonicity or convexity, according to the present application, three medium layer defects are determined to exist; whether the distortion rate curve cluster graph exists a distortion rate curve less than 0 is judged, from Figure 11 It can be seen that the distortion rate curve cluster graph does not exist a curve less than 0; in the next step, the distortion rate curve cluster is classified according to whether the distortion rate curve intersects, the number II curve does not intersect with other curves, that is, the number II curve is the insulation layer defect, and in the other two intersecting curves, the number I curve has a larger value on the left side of the intersection point, and the number III curve has a smaller value on the left side of the intersection point, that is, the number I is the protective layer defect, and the number III is the working tube defect, and the above three medium layer defect comparison results are completely consistent with the icon. For Figures 5 to 10 , the three medium layer defect comparison results are completely consistent with the actual situation of the defect, and details are not repeated here.

[0048] The above examples are only exemplary embodiments of the present application, and are not used to limit the present application, and the protection scope of the present application is defined by the claims. Those skilled in the art can make various modifications or equivalent replacements to the present application within the spirit and protection scope of the present application, and the modification or equivalent replacement is also regarded as falling within the protection scope of the present application.​

Claims

1. A polyurethane thermal pipe medium layer defect contrast method based on pitch effect, characterized in that, The method comprises the following steps: Step 1, receiving inputted capacitance imaging detection signals under different electrode spacings; Step 2, taking the absolute value of the defect signal change |△Y of the capacitive imaging detection signal obtained in step 1 n , and determining whether |△Y n | is greater than or equal to a preset threshold P n ; if not, it is determined that no defect exists, and if yes, it is determined that a defect exists; Step 3, after determining the presence of a defect, the distortion rate RY is calculated for the capacitance image detection signal obtained in Step 1 n , RY at the center of the defect is extracted n , and the RY curve cluster is plotted at the same origin n ; Step 4, judging RY n whether the curve cluster has monotonicity or concave-convexity; if not, it is determined not to belong to the single medium layer defect; if yes, the next step is performed; Step 5, judge RY n Whether there is a RY less than 0 in the curve cluster n If yes, then determine this RY n The curve is a polyurethane pipe protective layer defect, and the rest of RY n The curve is a RY with a larger value on the left side of the intersection point n The curve is a polyurethane pipe insulation layer defect, and the value of RY is smaller n The curve is a polyurethane pipe working tube defect; if not, go to the next step; Step 6, according to RY n Whether the curves intersect RY n Classify the curve cluster; non-intersecting RY n The curve is the polyurethane pipe insulation layer defect; the larger value on the left side of each intersection RY n The curve is the polyurethane pipe insulation layer defect, the smaller value RY n The curve is the polyurethane pipe working tube curve.

2. The polyurethane thermal pipe medium layer defect contrast method based on pitch effect according to claim 1, characterized in that, The detection signal of the capacitive sensor under different electrode spacings in step 1 includes a detection signal Y of the capacitive sensor detecting a polyurethane insulation tube with three medium layer defects under a limited number of continuously increasing electrode spacings n and a detection signal YS of the capacitive sensor detecting a polyurethane insulation tube without defects under different electrode spacings n .

3. The method according to claim 2, wherein the method is a polyurethane thermal insulation pipe medium layer defect contrast method based on pitch effect. The absolute value of the defect signal change |△Y n | = |Y n - Ys n | 4. The polyurethane thermal pipe medium layer defect contrast method based on pitch effect according to claim 1, characterized in that, The preset threshold value P in step 2 n The detection signal YS of the defect-free polyurethane insulation pipe is detected according to the capacitance sensor under different electrode spacings n The preset threshold value P is set n .

5. The method according to claim 1, wherein the method is characterized by, In step 3, the distortion rate RY n =(Y n -YS n ) / YS n RY at the center of the defect n The RY represents the maximum or minimum value of the distortion rate. n The curve cluster diagram is formed by discrete defect centers RY. n The values ​​are fitted together.

6. The method according to claim 1, wherein the method is characterized by, The absolute value of the defect signal change |△Y in step 2 n The distortion rate RY in step 3 n The judgment RY in step 4 n Whether the curve cluster has monotonicity or convexity is determined by means of Excel software, LabVIEW software, MathType software, MATLAB software and Python software at the same time to ensure the accuracy of the determination.

7. Use of a pitch effect based polyurethane thermal pipe medium layer defect contrast method according to any one of claims 1 to 6, characterized in that, The method is applied to defect judgment of polyurethane insulation pipes containing three medium layer defects under multiple electrode spacings.

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