Early warning method for centralized outbreak period of fatigue cracks of semi-rigid base asphalt pavement

Abstract

The invention discloses a semi-rigid base asphalt pavement fatigue crack concentrated outbreak period early warning method, which comprises the following steps: based on the structure type and the service life of a target pavement, determining the macroscopic development stage of a transverse crack, identifying a road section in a gentle development stage with a relatively slowed crack propagation rate, and performing early warning on the road section in the gentle development stage; taking as a potential risk paragraph; carrying out crack density detection on a smooth development stage road section, calculating the total length of cracks in a unit area as a crack surface density index, and comparing the index with a preset first-level threshold value to preliminarily evaluate the macroscopic crack development degree; the method comprises the following steps: drilling an asphalt surface layer core sample at a representative crack position of a road section, extracting an upper surface layer asphalt mortar material, testing a complex shear modulus and a phase angle through a rheological test, and calculating a microcrack early warning index reflecting the fatigue performance of the material based on the complex shear modulus and the phase angle; dividing the microcrack early-warning indexes into different early-warning grades according to the numerical range of the microcrack early-warning indexes; according to a comparison result of a crack surface density index and a preset threshold value, a differentiated pavement detection frequency, a coring period or a maintenance engineering strategy is formulated according to different early warning levels and crack density combinations; the method does not need complex model fitting, and is suitable for normalized management and maintenance practice of a large-scale road network.

Description

Technical Field

[0001] This invention relates to the field of road engineering technology, specifically to an early warning method for the concentrated outbreak of fatigue cracks in semi-rigid base asphalt pavements. Background Technology

[0002] Cracks are one of the most representative structural defects in semi-rigid base asphalt pavements. Failure to scientifically identify and proactively intervene in the early stages of crack evolution will accelerate the accumulation of fatigue damage in the structural layers, significantly shorten the pavement's service life, and increase the difficulty and social cost of later maintenance. Although pavement inspection technology has continuously improved in recent years, and automated inspection equipment and evaluation indicators are widely used, the current early warning and maintenance decision-making system for crack-related defects still faces the following key bottlenecks:

[0003] (1) Delayed identification of defects and lack of ability to perceive the evolution process: Existing detection methods mostly focus on the appearance of cracks (such as length, width and density), and record the current status of defects in a static snapshot manner. They cannot capture the dynamic evolution law of cracks from micro-crack initiation to macro-expansion. Maintenance decisions are often based on the fact that defects have been concentrated and it is difficult to achieve forward-looking intervention. (2) Single evaluation dimension and neglect of material performance degradation mechanism: Mainstream maintenance assessment relies on road surface detection indicators such as PCI and TCS. Although these indicators are easy to quantify, they cannot reflect the mechanical property deterioration of asphalt surface materials due to aging and fatigue. Since the damage state at the material scale is not included in the early warning system, the judgment of crack outbreak risk lacks a physical basis, and maintenance measures are often out of touch with the actual defect mechanism. (3) Disconnect between early warning and response and lack of graded response mechanism: Even if some road sections are identified as high risk, the existing process lacks differentiated response strategies based on risk level. Either there is an over-reliance on experience-based "one-size-fits-all" maintenance, resulting in waste of resources; or the lack of clear thresholds delays the intervention time and misses the best prevention window. The aforementioned problems collectively lead to a passive cycle in traditional maintenance models, where problems are discovered only to worsen, and repairs are only to require rework. Summary of the Invention

[0004] Purpose of the invention: The purpose of this invention is to provide an early warning method for the concentrated outbreak of fatigue cracks in semi-rigid base asphalt pavements. By combining crack development stage, crack surface density (SFD), and microcrack warning index (MCI), this method can provide accurate early warning at different stages of pavement crack development, identify potential crack propagation risks in advance, and formulate differentiated maintenance strategies, thereby solving the problems existing in the background technology.

[0005] Technical solution: The present invention provides an early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement, comprising the following steps:

[0006] (1) Based on the structural type and service life of the target pavement, determine the macroscopic development stage of its transverse cracks, identify road sections in a relatively slow-down development stage of crack propagation rate as potential risk sections.

[0007] (2) Crack density detection is carried out on road sections in the gradual development stage. The total length of cracks per unit area is calculated as the crack surface density index, and the index is compared with the preset first-level threshold to preliminarily assess the degree of macroscopic crack development.

[0008] (3) Select representative crack locations on the road section to drill core samples of the asphalt surface layer, extract the asphalt mortar material of the surface layer, test its complex shear modulus and phase angle through rheological tests, and calculate the microcrack early warning index reflecting the fatigue performance of the material based on the two.

[0009] (4) Based on the numerical range of the microcrack early warning index, it is divided into different early warning levels; then, based on the comparison results of the crack surface density index and the preset threshold in step (2), differentiated pavement inspection frequency, core sampling cycle or maintenance engineering strategy is formulated for different early warning levels and crack density combinations.

[0010] Furthermore, in step (1), the macro-development stages include the initial stage with a small number of cracks and slow growth, the rapid development stage with a surge in the number of cracks, the gradual development stage with a slowdown in the crack expansion rate, and the secondary acceleration stage where cracks expand rapidly again until they erupt in a concentrated manner.

[0011] Furthermore, the stage is determined by matching the service life of the road surface with key time nodes preset based on the structure type; the key time nodes include the first node that marks the entry into the slow development stage and the second node that marks the entry into the second accelerated development stage.

[0012] Furthermore, in step (2), the crack surface density index comprehensively considers the length of transverse cracks, longitudinal cracks, and strip repairs.

[0013] Furthermore, in step (2), the preset first-level threshold is used to determine whether the crack development has entered a precursor state of secondary accelerated development.

[0014] Furthermore, in step (3), the microcrack early warning index is obtained by squaring the product of the complex shear modulus and the sine of the phase angle, i.e., the complex shear modulus G is measured. * Calculate G using the value of the phase angle δ. * The square of sinδ, MCI, is a key indicator reflecting the mortar-scale fatigue performance of in-service asphalt pavement and is used for early warning of crack development.

[0015] Furthermore, in step (4), the warning level of the microcrack warning index is determined by comparing its value with a preset second-level threshold range.

[0016] Furthermore, in step (4), the differentiated strategy is as follows: when the crack surface density is lower than the first-level threshold, measures are taken according to different microcrack warning index levels, such as maintaining the regular detection frequency and extending the core sampling cycle, increasing the detection frequency and implementing annual core sampling, or initiating structural stability assessment to determine the repair plan; when the crack surface density reaches or exceeds the first-level threshold, measures are taken according to different microcrack warning index levels, such as implementing preventive maintenance, initiating structural stability assessment to determine the repair plan, or formulating a major overhaul and maintenance plan.

[0017] An electronic device according to the present invention includes a memory and a processor. The memory stores a computer program, and the processor executes the program to implement the steps of the method.

[0018] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method.

[0019] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: More accurate and proactive early warning: Breaking through the traditional reliance on the lagging judgment of macroscopic cracks, by integrating crack evolution stage identification and mortar-scale material performance (MCI) assessment, it achieves early identification of the concentrated outbreak period of fatigue cracks, significantly improving the timeliness of early warning; More scientific decision-making and more appropriate measures: Establishing a three-level early warning threshold system based on the linkage of SFD and MCI dual indicators, and formulating differentiated detection frequencies and maintenance strategies for different risk levels, avoiding "over-maintenance" or "under-maintenance", and improving resource utilization efficiency; Strong operability and easy implementation: The process is clear and the indicators are measurable (SFD can be obtained through automated detection, and MCI is based on standard DSR tests), without the need for complex model fitting, and is suitable for the routine maintenance practice of large-scale road networks. Attached Figure Description

[0020] Figure 1 This is a flowchart of the present invention;

[0021] Figure 2 This is a schematic diagram illustrating the four-stage development pattern of cracks according to the present invention;

[0022] Figure 3 This is a schematic diagram of the crack surface density (SFD) and the microcrack early warning index (MCI) kernel density of the present invention.

[0023] Figure 4 This is a schematic diagram of the operation process of the early warning method of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0025] like Figure 1 As shown in the figure, this invention provides an early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement, comprising the following steps:

[0026] Step 1: Four-stage judgment and initial screening of road sections: First, data is collected to obtain basic information about the target road section, including: pavement structure type (such as double-layer modified asphalt pavement, single-layer modified asphalt pavement) and service life.

[0027] Next, node matching is performed, matching key time nodes (Y2, Y3) according to the pavement structure type. Based on the service life and crack development rate patterns of numerous semi-rigid base asphalt pavements, the crack development process is divided into four stages, such as... Figure 2 As shown, the cracks are divided into four stages: the initial stage, the rapid development stage, the gradual development stage, and the secondary acceleration development stage. Node Y2 marks the transition from the "rapid development stage" to the "gradual development stage," meaning the crack growth rate begins to slow down. Node Y3 marks the transition from the "gradual development stage" to the "secondary acceleration stage," meaning the crack growth rate increases significantly again. For two-layer modified asphalt pavements, Y2 is 10 years and Y3 is 16 years. When the service life meets the condition Y2 < service life ≤ Y3, it is considered to be in the gradual development stage.

[0028] Finally, a stage determination is made by comparing the service life with the milestones to determine the current stage. Y2 < service life ≤ Y3: a stage of gradual development. Road sections in this stage are initially identified as having potential early warning needs and are included in the next step.

[0029] Step 2: Crack surface density (SFD) testing

[0030] Crack density (SFD) is calculated for road sections in the "gradual development stage". Crack density (SFD) refers to the total length of cracks (transverse cracks, longitudinal cracks, and strip repairs) per unit area. It serves as an indicator to quantify the degree of crack development in a specific area. The calculation formula is shown in Equation 1.

[0031] (1)

[0032] In the formula, Crack surface density (cm / m) 2 ); The total length (cm) of the cracks (horizontal cracks, longitudinal cracks, and strip repairs); Target road surface area (m²) 2 ).

[0033] Kernel density based on MCI and SFD, such as Figure 3As shown, the warning threshold for SFD was established at 4.75 cm / m. 2 The SFD was compared with a preset threshold of 4.75 cm / m. 2 A comparison was made, and a core sampling test was conducted once that year.

[0034] Step 3: Microcrack Early Warning Index (MCI) Test: Select 3-4 representative crack locations on the target road section. Drill asphalt pavement core samples from the middle and tail of the cracks, extract the top layer asphalt mortar, and use DSR (Dynamic Shear Rheometer) to test the Microcrack Early Warning Index (MCI). Specimen preparation, material performance testing, and MCI acquisition are carried out according to the following steps. Asphalt Mortar Extraction Method: Extract asphalt mortar samples from the cross-crack core samples of the asphalt pavement. Heat the top layer core sample at 130°C for 1.5 hours and sieve out coarse aggregate particles larger than 2.36 mm. Use rotary compaction to prepare large cylindrical specimens with a diameter of 100 mm and a thickness of 50 mm from the loose asphalt mortar. Drill small cylindrical specimens with a diameter of 12 mm and a height of 30 mm from the rotary compacted specimens for DSR (Dynamic Shear Rheometer) testing. Frequency sweep test: Using a DSR device, with test conditions of 15℃ and 10Hz, and a linear strain zone of 0.01%, frequency sweep tests were performed on small cylindrical specimens of asphalt mortar. The complex shear modulus G was measured. * Calculate G using the value of the phase angle δ. * The square of sinδ is MCI, which is a key indicator reflecting the dimensional fatigue performance of mortar in in-service asphalt pavement and is used for early warning of crack development.

[0035] Step 4: MCI Threshold Determination: Based on the kernel density map of MCI and SFD, such as... Figure 3 As shown, the warning threshold range for MCI has been established. The MCI warning classification criteria are as follows:

[0036] Grade A: MCI less than 2.63 × 10 20 Pa 2 ;

[0037] Grade B: MCI greater than or equal to 2.63 × 10 20 Pa 2 And less than 4.25×10 10 Pa 2 ;

[0038] Class C: MCI greater than or equal to 4.25 × 10 10 Pa 2 .

[0039] Step 5: Differentiated Response Strategy: Determine the risk level based on the MCI's A / B / C three-tier thresholds, and formulate differentiated detection and maintenance strategies in conjunction with the SFD level:

[0040] When the crack surface density (SFD) is less than 4.75 cm / m 2 hour:

[0041] MCI is Grade A: SFD is monitored based on the regular inspection frequency (twice a year); when SFD < 4.75 cm / m 2 When the core sample is taken every 2 years, a coring test should be conducted; when the SFD ≥ 4.75 cm / m 2 At that time, one core sampling test was conducted, and the surface density (SFD) of the fracture was ≥4.75 cm / m. 2 MCI level determination at that time;

[0042] MCI is grade B: tested quarterly (4 times a year), with SFD monitored; when SFD < 4.75 cm / m 2 When the core sample is taken once a year, the core sample should be taken once a year; when the SFD ≥ 4.75 cm / m 2 At that time, one core sampling test was conducted, and the surface density (SFD) of the crack was ≥4.75 cm / m. 2 MCI level determination at that time;

[0043] MCI Level C: Conduct an overall structural stability evaluation of the surface layer, and based on the performance of the middle and lower layers, identify the structural layers that need repair and develop a targeted maintenance plan.

[0044] When the crack surface density (SFD) is ≥ 4.75 cm / m 2 hour:

[0045] MCI is Grade A: Take preventative maintenance measures;

[0046] MCI is Grade B: Conduct an overall structural stability evaluation of the surface layer, and in conjunction with the performance of the middle and lower layers, identify the structural layers that need to be repaired and formulate a targeted maintenance plan;

[0047] MCI is Class C: Develop a major overhaul and maintenance plan.

[0048] Step 6: Early Warning Method Flowchart: as follows Figure 4 As shown, the overall process of the early warning method of this invention includes four sequentially connected steps: First, the development stage of cracks is determined by the service life and structural type, and potential risk sections in a slow development stage are screened out; then, crack surface density (SFD) is periodically tested and initially screened for these sections; next, core sampling tests are conducted to obtain the microcrack early warning index (MCI); finally, based on the classification results of SFD and MCI, differentiated monitoring and maintenance response strategies are formulated. This process realizes a closed-loop early warning from macroscopic defect identification to material performance evaluation, with clear logic, strong operability, and ease of engineering application.

[0049] This invention breaks through the limitations of traditional maintenance decision-making methods that rely solely on road surface defect detection. It constructs a three-level linkage early warning mechanism of "stage screening - initial screening by detection - precise material judgment". By integrating the macroscopic evolution law of cracks with the deterioration characteristics of mortar-scale material properties, it achieves early identification and precise intervention during the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavements, significantly improving the scientific nature, pertinence and timeliness of preventive maintenance.

Claims

1. A method for early warning of the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavements, characterized in that, Includes the following steps: (1) Based on the structural type and service life of the target pavement, determine the macroscopic development stage of its transverse cracks, identify road sections in a relatively slow-down development stage of crack propagation rate as potential risk sections. (2) Crack density detection is carried out on road sections in the gradual development stage. The total length of cracks per unit area is calculated as the crack surface density index, and the index is compared with the preset first-level threshold to preliminarily assess the degree of macroscopic crack development. (3) Select representative crack locations on the road section to drill core samples of the asphalt surface layer, extract the asphalt mortar material of the surface layer, test its complex shear modulus and phase angle through rheological tests, and calculate the microcrack early warning index reflecting the fatigue performance of the material based on the two. (4) Based on the numerical range of the microcrack early warning index, it is divided into different early warning levels; Based on the comparison results between the crack surface density index and the preset threshold in step (2), differentiated pavement inspection frequency, core sampling cycle or maintenance engineering strategies are formulated for different warning levels and crack density combinations.

2. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (1), the macro-development stages include the initial stage with a small number of cracks and slow growth, the rapid development stage with a surge in the number of cracks, the gradual development stage with a slowdown in the crack expansion rate, and the secondary acceleration stage with cracks expanding rapidly again until they erupt in a concentrated burst.

3. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 2, characterized in that, The stage is determined by matching the service life of the road surface with key time nodes preset based on the structure type; the key time nodes include the first node that marks the entry into the slow development stage and the second node that marks the entry into the second accelerated development stage.

4. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (2), the crack surface density index takes into account the length of transverse cracks, longitudinal cracks and strip repairs.

5. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (2), the preset first-level threshold is used to determine whether the crack development has entered a precursor state of secondary accelerated development.

6. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (3), the microcrack early warning index is obtained by squaring the product of the complex shear modulus and the sine of the phase angle, i.e., the complex shear modulus G is measured. * Calculate G using the value of the phase angle δ. * The square of sinδ, as a key indicator reflecting the dimensional fatigue performance of mortar in in-service asphalt pavement, is used for early warning of crack development.

7. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (4), the warning level of the microcrack warning index is determined by comparing its value with the preset second-level threshold range.

8. The early warning method for the concentrated outbreak period of fatigue cracks in semi-rigid base asphalt pavement according to claim 1, characterized in that, In step (4), the differentiated strategy is to take measures such as maintaining the regular detection frequency and extending the core sampling cycle, increasing the detection frequency and implementing annual core sampling, or initiating structural stability assessment to determine the repair plan when the crack surface density is lower than the first level threshold, according to different microcrack early warning index levels; when the crack surface density reaches or exceeds the first level threshold, measures such as implementing preventive maintenance, initiating structural stability assessment to determine the repair plan, or formulating major overhaul and maintenance plan are taken according to different microcrack early warning index levels.

9. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the program to implement the steps of the method according to claims 1-8.

10. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the steps of the method described in claims 1-8.

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