Loading...
5 results
Search Results
Now showing 1 - 5 of 5
- Validação de um método indireto de auscultação de degradações para avaliação da qualidade de pavimentos aeroportuáriosPublication . Feitosa, Ianca Teixeira; Santos, Bertha Maria Batista dos; Almeida, Pedro Gabriel de Faria Lapa Barbosa deO presente estudo tem como objetivo contribuir para melhorar o desempenho da componente “Avaliação do estado dos pavimentos” de um Sistema de Gestão de Pavimentos Aeroportuários (SGPA), através da validação de um sistema de levantamento indireto com recurso a veículo equipado, de baixo custo, que permite que os dados de degradação da superfície do pavimento sejam recolhidos rapidamente. Esta é uma componente particularmente importante do SGPA, uma vez que a partir dos dados recolhidos é possível avaliar o estado dos pavimentos e definir estratégias de intervenção. Para o efeito, o estudo apresenta dois métodos para recolha de dados de degradações superficiais de pavimentos flexíveis aeroportuários, aplicados na pista principal do Aeroporto Internacional Amílcar Cabral (AIAC), localizado na Ilha do Sal, Cabo Verde. Os métodos utilizados foram a inspeção visual tradicional realizada a pé e o método indireto de inspeção com recurso a veículo equipado com captura e gravação de imagem, feixes lasers e dispositivos de localização (GNSS) que se pretende validar. Para atingir o objetivo do trabalho, é introduzida a metodologia de gestão prática e sustentada de pavimentos aeroportuários, descrevendo as principais componentes de um SGPA; o processo para a obtenção do Pavement Codition Index (PCI), de acordo com a norma ASTM D 5340-12 (2012); a evolução e a importância da escolha adequada dos métodos de auscultação de pavimentos; e o procedimento de análise estatística de comparação entre duas amostras. Os princípios e metodologias descritos foram aplicados no desenvolvimentos do caso de estudo. A validação do método indireto de recolha de dados é analisada por comparação estatística dos dados coleta dos sobre as degradações superficiais do pavimento, precisamente a densidade da degradação por nível de gravidade, e os valores do índice PCI obtidos com os dois métodos. O estudo evidenciou dois aspetos que precisam ser aprimorados no sistema proposto, a qualidade das imagens capturadas para identificar degradações com nível de gravidade baixo e o treinamento do inspetor para alocação adequada dos níveis de gravidade durante a análise de imagens. Diferenças estatisticamente não significativas entre os conjuntos de resultados, validaram o método indireto proposto, resultando em vantagens significativas em relação à quantidade de área de pavimento inspecionada (maior), tempo de inspeção (menor), custo da recolha de dados, processamento e visualização de resultados (em um SIG), possibilidade de reavaliação dos dados (possível no método indireto) e controle de qualidade na identificação e medição das degradações. Tendo em conta os resultados obtidos, é ainda apresentado um estudo exploratório das melhorias introduzidas na estrutura e equipamento utilizado no método indireto de levantamento, onde é feita uma comparação da qualidade de imagem captada no levantamento das degradações observadas e dados coletados sobre as degradações, com vista à validação completa do método de auscultação de degradações da superfície de pavimentos proposto.
- Automated and Intelligent Inspection of Airport Pavements: A Systematic Review of Methods, Accuracy and Validation ChallengesPublication . Feitosa, Ianca; Santos, Bertha; Almeida, Pedro G.; mdpiAirport pavement condition assessment plays a critical role in ensuring operational safety, surface functionality, and long-term infrastructure sustainability. Traditional visual inspection methods, although widely used, are increasingly challenged by limitations in accuracy, subjectivity, and scalability. In response, the field has seen a growing adoption of automated and intelligent inspection technologies, incorporating tools such as unmanned aerial vehicles (UAVs), Laser Crack Measurement Systems (LCMS), and machine learning algorithms. This systematic review aims to identify, categorize, and analyze the main technological approaches applied to functional pavement inspections, with a particular focus on surface distress detection. The study examines data collection techniques, processing methods, and validation procedures used in assessing both flexible and rigid airport pavements. Special emphasis is placed on the precision, applicability, and robustness of automated systems in comparison to traditional approaches. The reviewed literature reveals a consistent trend toward greater accuracy and efficiency in systems that integrate deep learning, photogrammetry, and predictive modeling. However, the absence of standardized validation protocols and statistically robust datasets continues to hinder comparability and broader implementation. By mapping existing technologies, identifying methodological gaps, and proposing strategic research directions, this review provides a comprehensive foundation for the development of scalable, data-driven airport pavement management systems.
- Statistical analysis of an in-vehicle image-based data collection method for assessing airport pavement conditionPublication . Feitosa, Ianca Teixeira ; Santos, Bertha; Gama, Jorge; Almeida, Pedro G.This study presents a comprehensive comparative statistical analysis to validate a novel in-vehicle image-based method for collecting pavement condition data in airport environments. It highlights the method’s potential to address key challenges faced by airport pavement managers, such as the need for continuous maintenance and the demand for fast, effective, and reliable inspection procedures. The in-vehicle system integrates laser scanning systems, image capture, and georeferencing devices to collect pavement distress data, and its accuracy and reliability are evaluated statistically. The primary objective is to validate and enhance this novel inspection approach, which shows strong potential as an effective alternative for comprehensive pavement evaluation, enabling continuous, rapid monitoring and the analysis of trends. Validation was performed by means of a detailed statistical comparison of pavement distress density on the main runway of Amílcar Cabral International Airport, Sal Island, Cape Verde, based on data collected using the proposed in-vehicle and the traditional on-foot inspection methods. Non-parametric repeated measures analysis (nparLD) showed statistically similar results between methods for 9 of 12 distress type-severity combinations (4 types × 3 levels), especially for medium and high severity cases, and that pavement section and method-section factors were significant in 10 and 9 of 12 cases, respectively, indicating spatial variability. Kruskal-Wallis tests were applied to each method separately. Significant section-based differences were found in 11 of 12 cases for the traditional method and in 2 of 12 cases for the in-vehicle image-based method, indicating greater sensitivity of the on-foot inspection to spatial variation in distress distribution. These findings support the statistical validation of the proposed method for practical application in airport pavement management. Furthermore, the comprehensive analysis, which included correlation and autocorrelation studies, revealed a bias in severity level assignment during traditional on-foot inspections. The findings highlight time-efficiency gains with the image-based method and suggest improvements, such as enhancing image quality and providing inspector training to increase the accuracy of severity level classification. These results offer valuable insights for airport pavement managers, contributing to improved safety, operational efficiency, and resilience in the face of growing air traffic demands.
- Validation of an indirect data collection method to assess airport pavement conditionPublication . Santos, Bertha; Almeida, Pedro G.; Feitosa, Ianca; Lima, DéboraIn this study the authors compare two methods for airport asphalt pavement distress data collection applied on the main runway of Amílcar Cabral international airport, located at Sal Island in Cape Verde. The two methods used for testing were traditional visual inspection (on-foot) and an indirect method using a vehicle equipped with image capture and recording, lasers and geolocation devices (in-vehicle inspection). The aim of this research is to contribute to the validation of the proposed low-cost in-vehicle pavement distress inspection system with semiautomatic data processing in order to be considered in the implementation of the pavement condition assessment component of airport pavement management systems (APMS). This is a particularly important component as from the collected distress data it is possible to assess the condition of the pavements and define intervention strategies. Validation of the indirect data collection method is evaluated by statistical comparison of the collected distress data and pavement condition index (PCI) obtained from both methods. Statistically non-significant differences between the result sets validate the proposed indirect method, however the analysis evidenced two aspects that need improvement in the proposed system, namely the quality of the captured images to identify distresses with lower severity level and inspector training for proper allocation of severity levels during image analysis. This results in significant advantages considering that the total amount of the runway pavement area is inspected. Inspection time is reduced and data collection cost can be reduced. Processing and results visualization on GIS environment allows revaluation of the dataset on the in-vehicle method. Data interpretation and measurements quality control becomes simpler and faster.
- Pavement Inspection in Transport Infrastructures Using Unmanned Aerial Vehicles (UAVs)Publication . Feitosa, Ianca; Santos, BerthaThe growing demand for the transportation of goods and people has led to an increasing reliance on transportation infrastructure, which, in turn, subjects the pavements to high traffic volumes. In order to maintain adequate service and safety standards for users, it is essential to establish effective maintenance strategies that ensure the preservation of pavement conditions. As a result, emerging innovations in pavement surface inspection methods, surpassing traditional techniques in terms of inspection and data processing speed and accuracy, have garnered significant attention. One such groundbreaking innovation in inspection systems that has been tested and used in recent years to assess infrastructure condition is the use of unmanned aerial vehicles (UAVs). This study aims to present a critical open-access literature review on the use of UAVs in the inspection of transportation infrastructure pavement in order to assess the type of equipment used, the technology involved, applicability conditions, data processing, and future evolution. The analysis of relevant literature suggests that the integration of intelligent technologies substantially enhances the accuracy of data collection and the detection of pavement distress. Furthermore, it is evident that most applications and research efforts are oriented towards exploring image processing techniques for the creation of 3D pavement models and distress detection and classification.