Method for analyzing blasting reason of high-pressure bypass pipeline

Abstract

According to the method for judging the blasting reason of the high-pressure bypass pipeline, provided by the invention, high-precision positioning of a blasting source and objective analysis of a failure mechanism are realized through a multi-source data fusion technology in combination with crack form quantitative analysis, wall thickness reduction spatial distribution modeling and a dynamic weight distribution model. According to the method, a crack propagation path inversion technology is combined with stress field simulation, a blasting point positioning error is reduced, contribution degree weights of core factors such as wall thickness reduction and material deterioration are dynamically distributed by establishing a spatial correlation analysis model of evaluation parameters, the problem that traditional experience sorting is high in subjectivity is solved, and the method is suitable for large-scale popularization and application. Furthermore, based on a quantitative judgment rule of creep-fatigue competitive failure, the failure mode diagnosis accuracy is improved, and the service life of equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the field of safety assessment of thermal power generation equipment, and in particular to a method for analyzing the cause of explosion of a high-pressure bypass pipeline. Background Art

[0002] As a crucial foundation and pillar industry for my country's economic development, a stable supply of electricity is crucial. Despite the widespread adoption of clean energy sources such as wind and solar power in recent years, thermal power still accounts for approximately 50% of my country's electricity generation, and thermal power units are expected to maintain their dominant position for a long time to come. The high-voltage bypass system is a critical component during the startup, operation, and shutdown of thermal power units, and its safety and reliability directly impact the stable operation of the units.

[0003] The existing technology has the following deficiencies:

[0004] Crack analysis is highly subjective: it relies on manual measurement of crack length and cannot quantify morphological characteristics such as bifurcation angle and tortuosity (the error of traditional methods is ≥15%).

[0005] Wall thickness assessment is not intuitive: the discrete measurement point data lack spatial correlation, making it difficult to identify the thinning rate distribution pattern (spatial interpolation RMSE ≥ 0.25).

[0006] Low failure diagnosis accuracy: Failure mode classification is dominated by empirical judgment and lacks support from quantitative indicators such as fractal dimension and Weibull risk model (accuracy ≤ 80%).

[0007] Lack of multi-factor coupling analysis: It is difficult to objectively prioritize factors such as overheating, stress concentration, and material degradation (contribution ranking error ≥ 15%).

[0008] Therefore, a method is needed to comprehensively analyze the causes of high-pressure bypass pipeline explosion. Summary of the Invention

[0009] In a first aspect of the present disclosure, a method for determining the cause of a high-pressure bypass pipeline explosion is provided, comprising the following steps:

[0010] Acquire a crack region image and wall thickness measurement data of the high-pressure bypass pipeline, extract the geometric parameters of the crack based on the crack region image, including length, bifurcation angle, and fractal dimension, and calculate the thinning rate of each measuring point based on the wall thickness measurement data and generate a spatial distribution map of the thinning rate;

[0011] Analyzing the crack propagation characteristics according to the fractal dimension, combining the bifurcation angle and the thinning rate spatial distribution map, and determining the location of the blasting point through crack path reconstruction and stress concentration area simulation;

[0012] The wall thickness reduction rate, material spheroidization grade, residual stress, and operating time were selected as evaluation parameters. A spatial distribution correlation model between each parameter and the blasting point was established, and the contribution of each evaluation parameter was calculated.

[0013] Parameters exceeding a set threshold value from the evaluation parameters are extracted as target parameters, and a competitive ratio of the creep damage accumulation degree to the fatigue damage accumulation degree under the target parameters is calculated to determine the cause of the rupture of the high-pressure bypass pipeline.

[0014] In combination with the first aspect, analyzing the crack propagation characteristics according to the fractal dimension includes:

[0015] When the fractal dimension exceeds the first set threshold, it is determined to be a crack growth mode dominated by ductile fracture;

[0016] When the fractal dimension does not exceed the first set threshold, combined with the comparison result of the bifurcation angle and the second set threshold, it is determined that the crack growth mode is dominated by brittle fracture.

[0017] In combination with the first aspect, the method for constructing the spatial distribution association model is:

[0018] The spatial correlation between the thinning rate distribution and the stress concentration area was evaluated by statistical analysis methods;

[0019] The weight distribution of evaluation parameters is adjusted based on the degree of correlation matching.

[0020] In conjunction with the first aspect, calculating the contribution of each evaluation parameter includes:

[0021] Assigning benchmark weights to each evaluation parameter;

[0022] Increase or decrease the weight value based on the spatial correlation between the parameter and the blast point.

[0023] In conjunction with the first aspect, the determination of the cause of the blasting includes:

[0024] When the target parameter is the wall thickness reduction rate and the preset conditions are met, it is determined to be a failure dominated by long-term service damage;

[0025] When the target parameter is the material spheroidization grade, the failure type is verified in combination with the material performance test results;

[0026] When the target parameter is residual stress or operating time, the fatigue damage effect is determined based on the cyclic loading characteristics.

[0027] In combination with the first aspect, the competition ratio is determined as follows:

[0028] Based on the relative proportional relationship between creep damage accumulation and fatigue damage accumulation, the dominant failure type is output;

[0029] When the relative proportion exceeds a set threshold, it is determined that the corresponding damage type is dominant.

[0030] Beneficial Effects: This disclosure provides a method for determining the cause of high-pressure bypass pipeline bursts. By integrating multi-source data fusion technology with quantitative analysis of crack morphology, spatial distribution modeling of wall thickness reduction, and a dynamic weight allocation model, this method achieves high-precision positioning of the burst origin and objective analysis of the failure mechanism. This method utilizes crack propagation path inversion technology combined with stress field simulation to reduce the error in locating the burst point. By establishing a spatial correlation analysis model for evaluation parameters and dynamically assigning contribution weights to core factors such as wall thickness reduction and material degradation, this method addresses the highly subjective nature of traditional empirical ranking. Furthermore, based on quantitative determination rules for creep-fatigue competitive failure, this method improves the accuracy of failure mode diagnosis and extends the service life of equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flowchart of a method for analyzing the causes of cracking of a steam pipe weld according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present disclosure.

[0033] The terms used in the embodiments of the present disclosure are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present disclosure. The singular forms "a," "the," and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0034] It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0035] like Figure 1 FIG. 1 is a method for determining the cause of a high-pressure bypass pipeline explosion according to an embodiment of the present disclosure, characterized in that it includes the following steps:

[0036] S101: Acquire a crack region image and wall thickness measurement data of a high-pressure bypass pipe, extract geometric parameters of the crack based on the crack region image, including length, bifurcation angle, and fractal dimension, and calculate the thinning rate of each measuring point based on the wall thickness measurement data and generate a thinning rate spatial distribution map;

[0037] Specifically, high-precision measuring tools (such as vernier calipers, 3D scanners) are used to accurately measure the size (length, width, depth) and position of cracks on the blasting straight pipe, and the direction (longitudinal, transverse or oblique) and distribution pattern of the cracks are recorded.

[0038] Use an industrial camera (resolution ≥ 12 million pixels) to photograph the crack area and save it in RGB format.

[0039] Digital image processing technology (such as ImageJ software) is used to perform grayscale threshold segmentation (threshold range 80-160) on high-definition photos of the crack area, and the crack length, bifurcation angle and extension path are automatically extracted.

[0040] The box counting method is used to calculate the fractal dimension of the crack image, and the formula is:

[0041]

[0042] Where N(∈) is the number of boxes with side length ∈ required to cover the crack.

[0043] Along the longitudinal direction of the blasting straight pipe behind the high-pressure bypass valve, at intervals of 0.5m, use wall thickness measuring instruments and other equipment to measure the wall thickness of the edge of the blasting hole at each measuring point in turn.

[0044] The wall thickness measurement of the burst edge is carried out at multiple key positions of the burst edge (such as the top, bottom, and both sides) to avoid the limitation of a single position.

[0045] At the same time, the wall thickness of the outer wall of the blasted straight pipe is measured in a grid pattern. The measuring points are arranged as cross intersections with a spacing of 0.5m in the longitudinal and circumferential directions of the straight pipe. A total of multiple measuring points are used to measure the wall thickness and calculate the thinning rate.

[0046] The spherical variogram (C0 = 0.05, C = 0.8, α = 2.5 m) was used to generate the spatial distribution map of the thinning rate.

[0047] S102: Analyzing the crack propagation characteristics according to the fractal dimension, combining the bifurcation angle and the thinning rate spatial distribution map, and determining the location of the blasting point through crack path reconstruction and stress concentration area simulation;

[0048] For example, when D>1.2, it is determined to be a ductile fracture (the crack path is tortuous and grain boundary sliding dominates);

[0049] When D≤1.2, combined with the bifurcation angle θ>30°, brittle fracture (rapid extension along the crystal) is determined.

[0050] The crack growth mode label (tough / brittle) is used to guide the subsequent simulation parameter settings (for example, ductile fracture requires consideration of plastic strain).

[0051] The spatial distribution map of the thinning rate is used to locate areas with severe wall thinning (for example, thinning rate > 15% is high risk).

[0052] Combined with the crack growth mode, potential failure areas can be screened (for example, if the superimposed thinning rate of the ductile fracture area is greater than 15%, the risk is doubled).

[0053] Furthermore, the coordinates of the thinning area are mapped to the stress concentration area, and the stress concentration coefficient is calculated based on the geometric deformation of the thinning area (such as the local wall thickness thinning becoming a cross-sectional mutation).

[0054] Output results include the coordinates of the crack origin point and the distribution of stress concentration areas.

[0055] If the region satisfies D>1.2 (toughness), thinning rate>15%, and stress concentration factor>2.0, the crack origin point is marked as the burst point;

[0056] If the region satisfies both D≤1.2 (brittleness) and the bifurcation angle θ>30°, even if the thinning rate is low (such as 10%), the crack origin point is still marked as the explosion point.

[0057] S103: selecting wall thickness reduction rate, material spheroidization grade, residual stress, and operating time as evaluation parameters, establishing a spatial distribution correlation model between each parameter and the blasting point, and calculating the contribution of each evaluation parameter;

[0058] Specifically, the wall thickness reduction rate (Δs), material spheroidization grade (S), residual stress (σ r ), running time (T) four indicators.

[0059] First, eliminate the dimensional differences of different indicators to make them comparable.

[0060] For the above indicators, the standardized formula is:

[0061]

[0062] For example, if Δs at a certain measurement point is 20% (maximum value 30%, minimum value 10%), then after normalization, it becomes: 30-10 / 20-10=0.5.

[0063] Calculate the information entropy e of each indicator j :

[0064]

[0065] n is the number of data points.

[0066] Calculate the weight w of each indicator j :

[0067]

[0068] Calculate the weighting matrix for each indicator:

[0069] v ij =x′ ij ×w j ,

[0070] Determine the positive ideal solution and negative ideal solution

[0071] Calculate the closeness C j :

[0072]

[0073] The C of each parameter j The values ​​are sorted from high to low, C j The higher the value, the greater the contribution of the parameter to the cause of blasting.

[0074] S104: extracting parameters exceeding a set threshold value from the evaluation parameters as target parameters, and determining the cause of the rupture of the high-pressure bypass pipeline by comparing the competitive ratio of the creep damage accumulation degree to the fatigue damage accumulation degree under the target parameters.

[0075] Extract the evaluation parameter C j Parameters with values ​​greater than the set threshold (e.g. Cj>0.7) ensure that the actual impact of the parameter is significant.

[0076] Based on the selected target parameters, the dominance of the damage type (creep / fatigue) caused by them is quantified and the failure mechanism is clarified.

[0077] Calculate the damage accumulation associated with the target parameter only:

[0078] Creep damage D c :

[0079]

[0080] P is the Larson-Miller parameter, T i is the temperature, t i is the running time, Δ ti is the over-temperature operation time in the i-th temperature interval.

[0081] Fatigue damage D f :

[0082]

[0083] C = 1.2 × 10 12, , m = 3.0, Δσ is the stress amplitude, n i Indicates the number of cycles experienced by the pipeline at the i-th stress level (stress amplitude Δσi). f,i It represents the fatigue life of the material (i.e. the maximum number of cycles that the material can withstand before failure) under the i-th stress level (stress amplitude Δσi).

[0084] Competition failure judgment: If D c / D f >1.5, it is determined to be creep-dominated; otherwise, it is fatigue-dominated.

[0085] Furthermore, the analysis of crack propagation characteristics based on fractal dimension includes:

[0086] When the fractal dimension exceeds the first set threshold, it is determined to be a crack growth mode dominated by ductile fracture;

[0087] When the fractal dimension does not exceed the first set threshold, combined with the comparison result of the bifurcation angle and the second set threshold, it is determined that the crack growth mode is dominated by brittle fracture.

[0088] The fractal dimension (D) distinguishes fracture modes by quantifying the geometric complexity of the crack path. When the fractal dimension exceeds the first set threshold (such as D = 1.2), it indicates that the crack propagation path is tortuous and there is significant grain boundary slip, and it is determined to be dominated by ductile fracture. Ductile fracture is usually accompanied by plastic deformation and is common in high-temperature or ductile materials. If the fractal dimension does not reach the threshold, further analysis is required in combination with the bifurcation angle: when the bifurcation angle exceeds the second set threshold (such as 30°), the crack rapidly propagates along the grain boundary, showing brittle fracture characteristics. Brittle fracture is more common at low temperatures or material embrittlement conditions, with straight crack paths and fewer bifurcations. This judgment method replaces the subjectivity of traditional metallographic analysis by quantifying morphological characteristics, thereby improving the objectivity of failure mode classification.

[0089] Furthermore, the method for constructing the spatial distribution association model is:

[0090] The spatial correlation between the thinning rate distribution and the stress concentration area was evaluated by statistical analysis methods;

[0091] The weight distribution of evaluation parameters is adjusted based on the degree of correlation matching.

[0092] This model uses statistical methods (such as the Pearson correlation coefficient or spatial overlay analysis) to assess the spatial consistency between the wall thinning rate and the stress concentration area. If the thinning rate distribution map highly overlaps with the stress concentration area obtained by finite element simulation (e.g., a correlation coefficient greater than 0.7), it indicates that the wall thinning significantly exacerbates local stress and its weight needs to be dynamically increased. For example, the baseline weight of the wall thinning rate is 0.35, which can be increased to 0.5 when the spatial matching degree is high. This method solves the problem of the lack of spatial correlation of traditional discrete measurement point data, intuitively reveals the synergistic effect of thinning and stress, and provides a basis for locating risk areas.

[0093] Furthermore, the calculation of the contribution of each evaluation parameter includes:

[0094] Assigning benchmark weights to each evaluation parameter;

[0095] Increase or decrease the weight value based on the spatial correlation between the parameter and the blast point.

[0096] Contribution calculation is a two-step process. First, a baseline weight is assigned to each parameter (e.g., Δs = 0.35, S = 0.28, σr = 0.22, T = 0.15), determining its initial importance based on expert experience or historical data. Second, the weight is dynamically adjusted based on the spatial correlation between the parameter and the blasting point. For example, if a parameter exhibits an abnormally high value near the blasting point (e.g., Δs is greater than 20% at all points around the blasting point), its weight is increased to 1.3 times the baseline value. This dynamic mechanism ensures that the model can adapt to different operating conditions, prioritizing the actual dominant factors and avoiding misjudgments caused by fixed weights.

[0097] Furthermore, the determination of the cause of the blasting includes:

[0098] When the target parameter is the wall thickness reduction rate and the preset conditions are met, it is determined to be a failure dominated by long-term service damage;

[0099] When the target parameter is the material spheroidization grade, the failure type is verified in combination with the material performance test results;

[0100] When the target parameter is residual stress or operating time, the fatigue damage effect is determined based on the cyclic loading characteristics.

[0101] The judgment rules are differentiated based on the target parameter type, for example:

[0102] Wall thickness reduction rate dominates: If Δs>20% and the contribution is the highest, it is directly determined to be failure caused by long-term service damage (creep or wear), and the pipe section needs to be replaced;

[0103] Material spheroidization level: When S>3, metallographic examination is required to confirm the degree of carbide spheroidization. If the spheroidization rate is >50%, the material is considered to be degraded and failed, and heat treatment repair is recommended.

[0104] Residual stress or operating time dominance: Cyclic loading characteristics, such as >100 starts and stops or stress amplitude >80 MPa, must be analyzed, combined with fatigue damage accumulation (Df) to determine fatigue failure. This multi-path rule covers common failure scenarios, ensuring comprehensive conclusions.

[0105] Furthermore, the competition ratio is determined as follows:

[0106] Based on the relative proportional relationship between creep damage accumulation and fatigue damage accumulation, the dominant failure type is output;

[0107] When the relative proportion exceeds a set threshold, it is determined that the corresponding damage type is dominant.

[0108] The competitive ratio (Dc / Df) determines the dominant factor by quantifying the relative strength of creep and fatigue damage. A threshold (e.g., 1.5) is set as the demarcation point: if the ratio is greater than 1.5, it indicates that the accumulated creep damage is much higher than fatigue damage, and the system is determined to be creep-dominated; otherwise, fatigue-dominated. For example, for a pipeline with Dc = 0.85 (12,000 hours of overheating) and Df = 0.18 (stress amplitude 80 MPa, 120 cycles), a ratio of 4.72 > 1.5 indicates creep dominance. This method avoids the risk of misjudging absolute damage values ​​through relative proportions and significantly improves the reliability of the conclusions when combined with fuzzy logic verification (e.g., confidence difference > 0.3).

[0109] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present disclosure, and should all be included in the scope of protection of the present disclosure.

Claims

1. A method for determining the cause of high-pressure bypass pipeline explosion, characterized in that: The following steps are involved: Acquire a crack region image and wall thickness measurement data of the high-pressure bypass pipeline, extract the geometric parameters of the crack based on the crack region image, including length, bifurcation angle, and fractal dimension, and calculate the thinning rate of each measuring point based on the wall thickness measurement data and generate a spatial distribution map of the thinning rate; Analyzing the crack propagation characteristics according to the fractal dimension, combining the bifurcation angle and the thinning rate spatial distribution map, and determining the location of the blasting point through crack path reconstruction and stress concentration area simulation; The wall thickness reduction rate, material spheroidization grade, residual stress, and operating time were selected as evaluation parameters. A spatial distribution correlation model between each parameter and the blasting point was established, and the contribution of each evaluation parameter was calculated. Parameters exceeding a set threshold value from the evaluation parameters are extracted as target parameters, and a competitive ratio of the creep damage accumulation degree to the fatigue damage accumulation degree under the target parameters is calculated to determine the cause of the rupture of the high-pressure bypass pipeline.

2. The method according to claim 1, characterized in that The analysis of crack expansion characteristics according to fractal dimension includes: When the fractal dimension exceeds the first set threshold, it is determined to be a crack growth mode dominated by ductile fracture; When the fractal dimension does not exceed the first set threshold, combined with the comparison result of the bifurcation angle and the second set threshold, it is determined that the crack growth mode is dominated by brittle fracture.

3. The method according to claim 1, characterized in that The method for constructing the spatial distribution association model is: The spatial correlation between the thinning rate distribution and the stress concentration area was evaluated by statistical analysis methods; The weight distribution of evaluation parameters is adjusted based on the degree of correlation matching.

4. The method according to claim 1, wherein The calculation of the contribution of each evaluation parameter includes: Assigning benchmark weights to each evaluation parameter; Increase or decrease the weight value based on the spatial correlation between the parameter and the blast point.

5. The method according to claim 1, wherein The determination of the cause of blasting includes: When the target parameter is the wall thickness reduction rate and the preset conditions are met, it is determined to be a failure dominated by long-term service damage; When the target parameter is the material spheroidization grade, the failure type is verified in combination with the material performance test results; When the target parameter is residual stress or operating time, the fatigue damage effect is determined based on the cyclic loading characteristics.

6. The method according to claim 1, wherein The competition ratio is determined as follows: Based on the relative proportional relationship between creep damage accumulation and fatigue damage accumulation, the dominant failure type is output; When the relative proportion exceeds a set threshold, it is determined that the corresponding damage type is dominant.

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