**1. Introduction**

Bridges are important infrastructures all over the world. We have invested and spent a lot of money in constructing them. Also we assign big budgets for their maintenance, repair and strengthening annually. Since the number of bridges is increasing the amount of money needed to preserve the existing bridges at minimum standard level is considerable. In order to make decision for optimal budgeting we should know how bridges respond to various kinds of deteriorating factors and what their current and future conditions will be.

Why bridges need maintenance, repair and strengthening depend on many factors. Deterioration of bridges is due to aging, material deterioration under environmental conditions, increasing traffic volume and higher weights of vehicles. There are many factors which are responsible to make decision what the current condition and/or rating of a bridge is. Practically to make logical and defendable decisions the main action is to inspect bridges. Inspection provides a lot of collected data that should be stored and retrieved at any required time to obtain useful and practical information regarding the bridge condition and its immediate need. At this stage and by appropriate information in hand it can be possible to predict the remaining service lives of bridges.

Bridges are susceptible to many defects during their service lives. The main common defects that occur on cast-in-place concrete slab (deck) bridges include: cracking, scaling, delamination, spalling, efflorescence, honeycombs, pop-outs, wear, collision damage, abrasion, overload damage, reinforcing steel corrosion (Chen & Duan, 2000; Hartle et al., 2002). These defects are symptoms showing some kinds of deteriorations. Inspectors should report these symptoms and consequently type of deterioration(s) should be diagnosed.

Inspecting a concrete bridge deck includes visual and advanced inspection methods. The inspection of concrete bridge deck for symptoms like cracks, spallings, and other defects is primarily a visual activity. However, hammers and chain drags can be used to detect areas of delamination. In addition, several advanced techniques are available for concrete bridge deck inspection. Nondestructive methods include: acoustic wave sonic/ultrasonic velocity measurements, electrical methods, electromagnetic methods, rebound and penetration methods, carbonation and so many others if needed (Hartle et al., 2002).

Visual inspection is the primary method used to evaluate the condition of the majority of the existing bridges. Visual inspection is a subjective assessment and it may have a significant

Fuzzy Inference System as a Tool for Management of Concrete Bridges 447

It is obvious that how and to what extents the above mentioned items can be fulfilled by the

In general, the condition of a BMS element is identified by condition states and corresponding condition state language. Each element has a range of minimum to maximum condition states. Information from each BMS element along with expert input to predict how the condition of that element will change over time is used in BMS computer programs. BMS programs can estimate future network funding levels based on the predicted future bridge conditions and the corresponding costs to repair or replace them (Washington State

Inspect bridge and record the deficient quantity for each element in the corresponding

Generally in advanced BMS there is a module named Bridge Health Monitoring System (BHMS). BHMS can be considered as one of the most important parts of a practical BMS.

In bridge structures there are many different unforeseen conditions that we do not have enough information about them. Although in design codes we are forced to consider some parameters or factors affecting structural behavior there are even more items that we cannot consider them practically. Therefore it is probable to have some risk for not fulfilling the complete standards of safety. Presently health and performance are described based on subjective indices which are not precise. In addition there are some possibilities for unobserved and undiscovered symptoms, deteriorations, and damages in bridge structures due to limited or no accessibility to some elements. The immediate consequence is that the real health index is not that thought and considered. This unwilling fact impacts the effectiveness and reliability of any managerial decision irrespective of sophistication in the management process. Moreover, even experienced engineers may find visual signs of defects, deterioration and damage and cannot be able to diagnose the causative mechanisms, or their impact on the reliability of the bridge and its global health. The global health of a bridge as a whole system, inclusive of the performance criteria corresponding to each limit states is actually what is needed for effective managerial decisions. There are needs of periodic inspections to detect deterioration resulting from normal operation and environmental attack or inspections following extreme events, such as earthquakes or hurricanes. To quantify these system performance measures requires some means to monitor and evaluate the integrity of bridge structures while in service (Wang & Zong, 2002). BHMS can help managers to

BHMS may also have other applications. For example any damage in some elements of a bridge has direct effect on its load bearing capacity especially vibration characteristics. In other words this effect can change the overall behavior of the bridge under loads which cause the bridge to vibrate. Based on this fact any method for damage detection which is

The following outline provides a short BMS summary for a typical inspection:

Identify the BMS elements that apply to the structure.

know about the healthiness of a bridge at any given time.

Determine the total quantity for each element.

**2.2 Bridge Health Monitoring System** 

available data.

Bridge Inspection Manual, 2010).

condition state.

impact on the diagnosis and decisions to be made. For example a defect reported from one inspector may be different from the others. In order to overcome this unwilling fact nondestructive testing methods have been suggested for objective inspection in recent decades. Although these methods are more accurate than visual inspection, there are some kinds of problems. Interpretation of their results needs experience together with the knowledge about deteriorations of bridge material and damage types of its elements. Therefore results of visual inspection and some nondestructive testing methods are inherently uncertain and vague. It is to notify that the linguistically describing results are more uncertain and vague. Degree of uncertainty and level of vagueness depend on many parameters such as inspector's experience, definition of symptom or deterioration type, level of defect categorizations and many others.

Among many methods it seems that models based on artificial intelligence which apply soft computing methods are more attractive for dealing with uncertain and vague data in managing bridges. Fuzzy Inference System (FIS) is capable of being used in areas for decision making when data is uncertain. One of the most attractive advantages of FIS is its tolerability to noisy (uncertain and vague) data.

Based on the type of problems with uncertain and vague data, different FIS modeling types can be regarded as appropriate and easy methods for managing bridges (Tarighat & Miyamoto, 2009).

After introduction section this chapter continues with section 2 and its subsections showing the need for managing bridges and introduces Bridge Management System and Bridge Health Monitoring system. Ambiguity in diagnosis and decision making based on the collected data in above mentioned systems are discussed in section 3. Section 4 explains why fuzzy inference systems are suitable in managing systems. Its subsections are about fuzzy inference systems including Mamdani's method and Adaptive Neuro Fuzzy Inference System (ANFIS) method. Then some case studies and some typical applications of fuzzy inference system for managing bridges are included in section 5. Section 6 concludes this chapter.
