Health Monitoring Of Civil Structures Research Articles

Conceptual design and preliminary characterization of serial array system of high-resolution MEMS accelerometers with embedded optical detection

This paper introduces a technology for robust and low maintenance cost sensor network capable to detect accelerations below a micro-g in a wide frequency bandwidth (above 1,000 Hz). Sensor networks with such performance are critical for navigation, seismology, acoustic sensing, and for the health monitoring of civil structures. The approach is based on the fabrication of an array of high sensitivity accelerometers, each utilizing Fabry-Perot cavity with wavelength-dependent reflectivity to allow embedded optical detection and serialization. The unique feature of the approach is that no local power source is required for each individual sensor. Instead one global light source is used, providing an input optical signal which propagates through an optical fiber network from sensor-to-sensor. The information from each sensor is embedded onto the transmitted light as an intrinsic wavelength division multiplexed signal. This optical "rainbow" of data is then assessed providing real-time sensing information from each sensor node in the network. This paper introduces the Fabry-Perot based accelerometer and examines its critical features, including the effects of imperfections and resolution estimates. It then presents serialization techniques for the creation of systems of arrayed sensors and examines the effects of serialization on sensor response. Finally, a fabrication process is proposed to create test structures for the critical components of the device, which are dynamically characterized.

A correlation between pulse diagnosis of human body and health monitoring of structures

The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back approximately five thousand years in the recorded history of China. With advances in the development of modern technology, the concept of health monitoring of a variety of engineering structures in several applications has begun to attract widespread attention. Of particular interest in this study is the health monitoring of civil structures. It seem natural, and even beneficial, that these two health-monitoring methods, one as applies to the human body and the other to civil structures, should be analyzed and compared. In this paper, the basic concepts and theories of the two monitoring methods are first discussed. Similarities are then summarized and commented upon. It is hoped that this correlation analysis may help provide structural engineers with some insights into the intrinsic concept of using pulse diagnosis in human health monitoring, which may of be some benefit in the development of modern structural health monitoring methods.

Health Monitoring for Civil Structures by Means of Acoustic Emission

Health Monitoring for Civil Structures by Means of Acoustic Emission

Fiber Optic Sensors for Bridge Monitoring

Advances in the production of optical fibers made possible the recent development of innovative sensing systems for the health monitoring of civil structures. The main reasons for this development are the reduced weight and dimensions of fiber optic sensors, the strong immunity to electromagnetic interference, the improved environmental resistance and the scale flexibility for small-gauge and long-gauge measurements. These systems can provide high-resolution and measurement capabilities that are not feasible with conventional technologies. In addition, they can be manufactured at a low cost and they offer a number of key advantages, including the ability to multiplex an appreciable number of sensors along a single fiber and interrogate such systems over large distances. For these reasons, it is evident that fiber optic sensors will change the instrumentation industry in the same way fiber optics has revolutionized communications. This paper provides an overview of the intensity modulated and spectrometric fiber optic sensors and techniques to assess the condition of existing structures in order to enhance the durability of the new bridges, increasing lifetime and reliability and decreasing maintenance activities. Application of these sensors to monitoring strain, temperature, inclination, acceleration, load measurements, ice detection, vehicles speeds and weights, and corrosion and cracking of reinforced and prestressed concrete structures will be described.

Self-referenced intensity-based fiber optic sensor system using fiber Bragg gratings

We present a method for measuring the intensity variation regarding the measured physical attributes of intensity-based fiber Bragg grating sensors. These sensors can be configured for multiplexing, thermal insensitivity, and immunity to noise from the light source and/or the lead-in/out fibers caused by the external load. To achieve these goals, the intensity-based optical fiber sensor is implemented between a pair of fiber Bragg gratings. Based on the ratio or dBm difference from the two reflecting intensities of the reference and the sensing fiber Bragg gratings, the appropriate measurable parameters associated with the intensity variations can be detected. Different from transmission type intensity-based sensors, a reflective type based on a pair of fiber Bragg gratings is introduced. To validate the proposed method, a transducer made by using an etched-cladding fiber is deposited onto the metal thin film for sensing metal corrosion. Based on the evanescent field of a fiber and a pair of fiber Bragg gratings, multiple embedded corrosion sensors could be designed for civil structural health monitoring. Also, the proposed method could be applied to a biosensing design on a transducer.

Health Monitoring of Civil Structures

Health monitoring of civil infrastructure systems is cost-effective and necessary since these systems are generally the most expensive investments/assets in any country. In the U.S. these assets are estimated at $20 trillion. In addition, these systems have long service life compared with any other kinds of commercial product, and are rarely replaceable once they are erected. Yet the feedback and controls on the "state of health" of constructed systems are practically nonexistent. Nondestructive evaluation (NDE), sensing and smart structures are essential parts of this feedback and monitoring system for infrastructures. The NSF NDE initiative as well as workshops and related awards/projects are described in this paper.

Regimes of elastohydrodynamic lubrication : JOHNSON, K. L. Journal of Mechanical Engineering Science, Vol 12, No 1 (Feb 1970) pp 9–16

The structural health monitoring of civil structures has been highlighted by the perception that the cost involved in the prevention of structural accidents is lower than the cost of correcting them. In addition, in the case of large structures (e.g. bridges, dams and industrial sheds), it is desired that the damage diagnosis should occur quickly from real-time monitoring without interrupting the use of the structure. The structural diagnosis may be performed based on vibration measurements, considering that the structural damages modify modal parameters of the structure (e.g. frequencies and mode shapes). With these dynamic responses, the application of appropriate computational tools to recognize and classify structural damage is intended, and artificial neural networks (ANN) have gained a lot of attention in achieving these goals. In this work, the methodology of diagnosing structures by real-time monitoring is originally developed and based on initial definition of the optimal topology, avoiding both the use of multiple hidden layers and the combination of several neural networks, and by applying of non-adaptive and adaptive first-order algorithms for agile network training, in order to be mathematically suitable for continuous and real-time monitoring, which allows updating both the dataset and neural parameters without greater computational effort. As some of these algorithms were not addressed in the diagnosis of civil structures with the aforementioned hypotheses, until this research, the performance of each algorithm was verified in case studies that simulate classic structural systems adopted in most civil buildings. Finally, the results endorse the feasibility of improving the structural diagnosis based on the training of a simple neural network, with one hidden layer, associated with non-adaptive or adaptive first-order optimizers that guarantee the agile assessment of structural integrity in real time.