Bridge management for the 21st century

Analysis of edge-detection techniques for crack identification in bridges

Abstract: Bridge monitoring and maintenance is an expensive yet essential task in maintaining a safe national transportation infrastructure. Traditional monitoring methods use visual inspection of bridges on a regular basis and often require inspectors to travel to the bridge of concern and determine the deterioration level of the bridge. Automation of this process may result in great monetary savings and can lead to more frequent inspection cycles. One aspect of this automation is the detection of cracks and deterioration of a bridge. This paper provides a comparison of the effectiveness of four crack-detection techniques: fast Haar transform (FHT), fast Fourier transform, Sobel, and Canny. These imaging edge-detection algorithms were implemented in MatLab and simulated using a sample of 50 concrete bridge images (25 with cracks and 25 without). The results show that the FHT was significantly more reliable than the other three edge-detection techniques in identifying cracks.

Reliability-based life-cycle management of highway bridges

Abstract: The objective of bridge management is to allocate and use the limited resources to balance lifetime reliability and life-cycle cost in an optimal manner. As the 20th century has drawn to a close, it is appropriate to reflect on the birth and growth of bridge management systems, to examine where they are today, and to predict their future. In this paper, it is attempted to shed some light on the past, present, and future of life-cycle management of highway bridges. It is shown that current bridge management systems have limitations and that these limitations can be overcome by using a reliability-based approach. It is concluded that additional research is required to develop better life-cycle models and tools to quantify the risks, costs, and benefits associated with highway bridges as well as their interrelationships in highway networks.

Cost-Reliability Interaction in Life-Cycle Cost Optimization of Deteriorating Structures

Abstract: Life-cycle cost analysis of deteriorating structures has to consider not only time-varying resistance and loading affecting the reliability of these structures but also maintenance interventions applied during their lifetime. Finding the optimum maintenance scenario for a deteriorating structure is a complex process involving the selection of maintenance interventions and their application times associated with minimum life-cycle cost. There is a cost relationship between maintenance intervention cost and the effect of the intervention on system reliability. However, this relationship is not included in modern structural management systems since costs of interventions are prescribed as fixed values independent on their effects on system reliability. Neglecting the interactions among maintenance interventions, their effects on structural performance, and corresponding costs leads to significant limitations of modern management systems for civil infrastructures. In this article, maintenance intervention cost is not considered to be fixed but evaluated dynamically by using cost functions according to time-dependent variables related to the quality of intervention. The main advantages of using cost functions are the flexibility and expandability required for general purpose reliability-based structure management systems. In fact, cost functions can be used in any structure management system based on life-cycle cost. A practical example is provided to show how to establish cost functions of maintenance interventions and how these functions can be used to obtain the optimal life-cycle maintenance scenario.

Evaluation of Expected Life-Cycle Maintenance Cost of Deteriorating Structures

Abstract: In a world where financial resources do not keep pace with the growing demand for maintenance of deteriorating structures, it is imperative that those responsible for maintenance decisions make the best possible use of limited financial resources. Decision makers have to evaluate the expected life-cycle maintenance cost of deteriorating structures and use benefit/cost techniques for finding the optimal resource allocation. This paper proposes a methodology for the evaluation of expected life-cycle maintenance cost of deteriorating structures by considering uncertainties associated with the application of cyclic maintenance actions. The methodology can be used to determine the expected number of maintenance interventions on a deteriorating structure, or a group of deteriorating structures, during a specified time horizon and the associated expected maintenance costs. The method is suitable for application to both new and existing civil infrastructures under various maintenance strategies. The ultimate objective is to evaluate the costs of alternative maintenance strategies and determine the optimum maintenance regime over a specified time horizon. In its present format, the first line of application of the method is for highway bridges. However, the method can be used for any structure, or group of structures, requiring maintenance in the foreseeable future. The proposed method can be programmed and incorporated into an existing software package for life-cycle costing of civil infrastructures. An existing reinforced concrete bridge stock is analyzed to illustrate the proposed methodology and to reveal the cost-effectiveness of preventive maintenance interventions.

An imaging data model for concrete bridge inspection

Abstract: Bridge management systems were developed to address the data organization and decision making aspects of bridge inspection and maintenance. However, these systems still neglect the automation aspects of bridge monitoring and inspection. Automation may result in monetary savings and can optimize the inspection process. This paper discusses the data model that was developed to support automated imaging inspection of concrete bridges. The paper discusses the framework for an automated bridge inspection methodology and provides a detailed discussion of the data modeling efforts involved in the development of the imaging information model.