Automated runway groove measurement and evaluation

Lin, Li; Wang, Kelvin C. P.; Li, Joshua; Luo, Wenting

doi:10.1007/s12205-016-0789-6

Cited by 7 publications

(12 citation statements)

References 6 publications

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“…Lee et al [17] used 3D laser equipment to collect indoor grooving model data and adopted section grooving depth and groove spacing indicators to verify the feasibility of using a 3D laser for grooving measurement. Li et al [18] and Kelvin et al…”

Section: Introductionmentioning

confidence: 99%

Quality Assessment of Milling Pavement Surface Using 3D Line Laser Technology

2018

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To ensure that a regular milled surface texture provides good bonding without residual distress, a new specification of milling surface assessment has been established for quantitatively evaluating the milled surface quality. This research explores the possibility of using three-dimensional (3D) laser scanning technology to develop an algorithm to obtain a milled surface model that can measure evaluating indicators, milling depth and texture depth, and identify poorly milled areas. A case study was conducted by using a laser scanning vehicular system to collect 3D continuous pavement transverse profiles data in a 500 m long segment of Highway S107. The results show that the proposed method is very promising and can measure the milling depth and texture depth to effectively and quantitatively differentiate between good-(milling depth between 47 mm and 53 mm and texture depth exceeding 2 mm) and poor-quality work. Moreover, the poorly milled areas such as those with residual distress and unmilled areas that will lead to premature failure can also be identified using the proposed method. The proposed method can effectively support remilling work and ensure the quality of the overlay pavement.

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Section: Introductionmentioning

confidence: 99%

Quality Assessment of Milling Pavement Surface Using 3D Line Laser Technology

2018

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“…Past studies indicate that groove dimensions can be automatically measured using point laser ranger-based profiling equipment and 3D laser imaging sensor-based instruments [ 11 , 12 , 13 , 14 , 15 ]. For the collected grooving data, the identification can be implemented in three phases, namely the potential dip identification, the determination of two endpoints of the identified dip, and true groove determination.…”

Section: Introductionmentioning

confidence: 99%

“…A dip and spike pair can be obtained when the gradient of each groove is calculated, and the forward and backward traversal technique are used to determine the two endpoint points of each groove. The last method is the geometry contour-based method [ 13 ], in which Euler-Bernoulli beam filter is developed to produce a filtered profile, and then the differences between the filtered profiles and the original profiles are calculated. The location of potential dips can be determined based on moving window length and the given threshold, in which one drawback exists: a proper threshold needs to be set to determine the deepest point of the potential dip.…”

Section: Introductionmentioning

confidence: 99%

“…The determination of the two endpoint positions of grooves is critical for the computation of groove dimension. Previous studies indicate there are three methods for the determination of two endpoints of grooves [ 11 , 12 , 13 , 14 ]. One is the cluster-based approach, in which the two endpoints of the groove depend on the number of points inside grooves [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…Since the low-pass based technique cannot efficiently eliminate the influences of narrow dips, thereby this method is not always effective for determination of two endpoints of grooves. The third method uses the forward and backward traversal techniques to determine the starting and ending points of each groove and produces a decent result in most cases [ 11 , 13 ]. However, this method can fail in some special cases, such as when the gradients vary from negative (positive) to positive (negative) at the location inside grooves.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Groove Measurement and Evaluation with High Resolution Laser Profiling Data

Lin

Luo

Wang

et al. 2018

Sensors

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Grooving is widely used to improve airport runway pavement skid resistance during wet weather. However, runway grooves deteriorate over time due to the combined effects of traffic loading, climate, and weather, which brings about a potential safety risk at the time of the aircraft takeoff and landing. Accordingly, periodic measurement and evaluation of groove performance are critical for runways to maintain adequate skid resistance. Nevertheless, such evaluation is difficult to implement due to the lack of sufficient technologies to identify shallow or worn grooves and slab joints. This paper proposes a new strategy to automatically identify airport runway grooves and slab joints using high resolution laser profiling data. First, K-means clustering based filter and moving window traversal algorithm are developed to locate the deepest point of the potential dips (including noises, true grooves, and slab joints). Subsequently the improved moving average filter and traversal algorithms are used to determine the left and right endpoint positions of each identified dip. Finally, the modified heuristic method is used to separate out slab joints from the identified dips, and then the polynomial support vector machine is introduced to distinguish out noises from the candidate grooves (including noises and true grooves), so that PCC slab-based runway safety evaluation can be performed. The performance of the proposed strategy is compared with that of the other two methods, and findings indicate that the new method is more powerful in runway groove and joint identification, with the F-measure score of 0.98. This study would be beneficial in airport runway groove safety evaluation and the subsequent maintenance and rehabilitation of airport runway.

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