Advances in sensors and information technologies have brought structural health monitoring (SHM) as a data-driven remedy for civil infrastructure safety. Smart and mobile sensor systems have taken SHM discipline to a new era in the past two decades. Smartphones, in parallel, have paved the milestones of innovative SHM applications empowered by smart, distributed, wireless, mobile, and participatory sensor networks. This chapter introduces the advent of smartphones as an SHM technology and describes crowd/citizen engagement into an SHM framework. In contrast with the traditional monitoring approaches, there is a lack of control in sensor operation in terms of time, location, duration, and coupling conditions. These discrepancies are formulated as citizen-induced uncertainties, and smartphone-centric multisensory solutions are proposed. Smartphone-based SHM can characterize cyberphysical civil infrastructure systems, e.g., updating numerical bridge models with crowdsourced modal identification results in an automated manner. The chapter concludes with the state-of-the-art vision for smartphone usage in SHM, near future trends, and finally long-term research directions.
Structural health monitoring (SHM) has the potential to transform the bridge engineering industry by providing stakeholders with additional information to inform decisions about the design, operation, and management of bridges throughout the structures’ lifespans. This chapter gives guidance on SHM for engineers who design, build, operate, and maintain bridges. There remain numerous technical challenges to overcome when deploying SHM systems; however the most important issues to consider are how to decide what information is required, and then how to develop a strategy to deliver this information in a form that is easy to interpret and can inform decision making. This chapter gives an introduction to the uses and current capabilities of SHM. Directions for future research and management of bridge SHM systems are also discussed.
A novel approach for implementing structural health monitoring systems for aerospace structures
SHM can be defined as automated methods for determining adverse changes in the integrity of mechanical systems. The objective of an SHM system is to provide an automated and real-time assessment of a structure’s ability to serve its intended purpose. The need for and the benefits of SHM systems for civil, military, and aerospace applications have been documented by many researchers. A typical SHM system consists of a diagnosis component (low level), which includes the levels of detection, localization, and assessment of any damage, and a prognosis component (high level), which involves the generation of information regarding the consequences of the diagnosed damage. Fig. 2.1 illustrates a notional SHM system. The current diagnostic component approach is to process sensory data using pattern recognition methods for classification of structural states. Training data is used to design a classifier, and the resulting classifier performance is evaluated by scoring the classification results from data not utilized during the design or training phases. Although information provided by the low levels of SHM could reduce inspection time and cost, low-level approaches have achieved only limited success to date . This is primarily due to the fact that these approaches require training data from all anticipated damage states and operational environments to be effective. Most research has focused on the low levels of SHM and very little attention has been given to the high levels in SHM. Information provided by the two higher levels of SHM relates to quantifying the degree of damage and ultimately provides an assessment of the consequences of damage in terms that are the most meaningful to maintainers, operators, and commanders for improvements in operation. Exploiting the full operational benefits of SHM requires a new methodology for information processing. CASE is well suited for this application and is discussed in the next section.
Recent advances and trends in structural health monitoring
Challenges for structural health monitoring
SHM is an efficient way to safeguard national property. Although SHM has various advantages, like maintaining only when required, which reduces capital expenditures and increases the life span and improves public safety, there are certain limitations of structural health monitoring. Limitations of SHM are that when neglected this can cause great damage to the structures as well as to public around it.
State that the failure of civil infrastructure systems to perform at their expected level might decrease the national gross domestic product by almost 1%. However, improved structural health monitoring of civil infrastructures can help in improving the performance ratio. Differences in the shapes and sizes of the structures and also the age of the structures influence the SHM technique involved. The differences make it difficult for establishing a standard method for all the structures, which could further save time and efforts. The type of SHM system applied on any structure is based on several factors like shape and size of the structure. The structural health monitoring of a bridge like Tsing Ma Bridge in Hong Kong and a building like Shanghai Tower in the same city will be different. The Tsing Ma Bridge is the longest suspension bridge in the city with the main span of 1377 m, and the Shanghai Tower is 632 m tall. The structural differences in these two buildings thus demand different types of SHM techniques to be used. The Tsing Ma is equipped with a wind and structural health monitoring system. The entire SHM system is comprised of 6 anemometers, 110 strain gauges, 115 temperature sensors, 3 data acquisition outstations, 2 displacement transducers, 19 accelerometers, 10 level sensing stations, 7 weigh-in-motion stations, and 14 GPS rover stations. The Shanghai Tower is monitored by a system comprised of 400 sensors of 11 types like the strain sensors, together with 11 substations.
Similarly, an old structure like Steccata church in Parma, Italy, and a new building constructed in the same city with similar environmental conditions will have different types of health monitoring systems involved. The church is monitored with a laser Doppler vibrometer technique, a noncontact detection technique providing data with great reliability and accuracy; in contrast, a recently constructed building will be installed with embedded sensors to measure the data.
The variations in the structures demand unique monitoring techniques to be employed with each structure. It becomes difficult when there is a lot of construction. Analyzing each structure individually is an enormous task and is prone to defects. Thus standard policies for employment of monitoring methods can save time and capital expenditures as well as reduce the errors involved in collection of measurement data.
Structural health monitoring (SHM) has the potential to transform the bridge engineering industry by providing stakeholders with additional information to inform decisions about the design, operation, and management of bridges throughout their life. This chapter gives guidance on SHM for engineers who design, build, operate and maintain bridges. There remain numerous technical challenges to overcome when deploying SHM systems, but the most important issues to be considered are how to decide what information is required and then how to develop a strategy to deliver this information in a form that is easy to interpret so as to inform decision making. This chapter presents a series of case studies to show how SHM systems can be used in practice to obtain valuable data and to explore the challenges faced during such projects. Future directions for emerging technologies and approaches for future research and management of bridge SHM systems are also discussed.