MS17.24 - Structural Health Monitoring

The major challenge in detecting the loss of tightening torque in bolted connections using indirect vibration measurements is the considerable variability and noise presented in the data. This issue is more complex, assuming a heterogeneous population of a set of bolted connections with incomplete data or unlabeled information, i.e., where only some torque conditions are known to train state classification algorithms. Thus, even training algorithms to recognize the loss of tightening torque, generalizations to similar structures are challenging to be produced without retraining these classifiers. This paper illustrates how we can use a population of vibration data measured at bolted joints to avoid this limitation. The key idea is to use the information from a classifier trained with data in a source structure, i.e., with available labeled data, and perform a domain adaptation for a target population of a similar setup with another bolted joint, where we do not have the tagged information previously. Various domain adaptation algorithms can be chosen, but here, a simple transfer component analysis (TCA) was demonstrated to be enough to transfer the information to detect the loss of tightening torque assuming a set of different structures. The method is exemplified in a group of three Orion beams with several tightening torques applied. The features used are the simple resonance frequencies extracted from the transmissibility functions. A Gaussian Mixture Model (GMM) is created to classify the states in a supervised mode using the source data. All detailed steps are carefully discussed with recommendations and advantages of this approach to implement this method.

The author has proposed a vehicle-based (coupling of a moving vehicle and a bridge) bridge health monitoring system by using public buses which is one practical solution to the problem for condition assessment of short and medium span(10-30m) bridges. The vehicle-based measurements with public buses as part of a public transit system are used to detect anomalies (deterioration) of the target bridge by analyzing long term vibration measurement data collected while the vehicle (bus) crossed the target bridges, mainly vertical acceleration da-ta, as obtained from the acceleration sensor installed under the rear wheel spring of an in-service fixed-route bus. Main reasons for using an in-service fixed-route bus (i.e. a heavy vehicle) are as follows: ① If a vehicle of about 10 m length is used for measurement, it is highly likely that the vehicle is alone on the lane when it crosses a short or medium span bridge, ② A relatively heavy vehicle is needed to produce significant vibration of short and medium span bridges which have relatively high flexural stiffness, ③ A fixed-route bus used as a source of bridge excitation, easily allows to reproduce measuring conditions such as the time of passage, route, frequency and velocity, ④ Since a fixed-route bus equipped with a sensor makes the rounds, it is possible to monitor mainly short and medium span bridges in a partic-ular area on a regular basis. As a result, substantial cost savings can be achieved because there is no need to install sensors to all bridges to be monitored, and ⑤ The electric power for the measuring instruments used can be supplied by the power supply of the bus. In this study, in order to evaluate the sensitivity of “characteristic deflection” which is a bridge health condition indicator used by the system, it has been field-tested over 10 years period by using an in-service fixed-route bus operating on a bus route in Ube city, Yamaguchi Prefecture, Japan. This paper describes not only the validation results obtained from the long-term monitoring and discusses the usefulness of the system but also the problems of the conventional observation method based on “characteristic deflection”, which is a bridge condition indicator that makes possible efficient detection of structural anomalies of the bridge being monitored, are identified, and a new observation method that enhances the damage detection sensitivity of the system is evaluated. As the results, it will be able to make a rational long-term health monitoring system for existing short and medium span bridges, and then the system helps bridge administrators to establish the rational maintenance strategies.

Researchers are increasingly interested in the project dedicated to developing and validating low-cost accelerometer prototypes based on Arduino technology. This growing interest stems from the fact that the use of low-cost solutions may make Structural Health Monitoring (SHM) practical and affordable to structures with limited funds for their health monitoring. However, many of the currently developed prototypes do not have comparable precision and resolution as those of the commercial alternatives. Furthermore, the noise density of these freshly de-signed sensors has not been tested in the laboratory. In truth, normally, the characteristic of the developed accelerometer is taken from the datasheet of the chipsets utilized to create the solu-tion. This paper presents consistent work with developing a low-cost remote accelerometer with a sampling frequency of 333 Hz and noise density of 51μg⁄√Hz. This accelerometer's accuracy, noise density, and reliability are evaluated through laboratory experiments. It is essential to mention that this accelerometer does not need any additional data acquisition equipment and is self-sufficient.