Ignacio Gonzalez

KTH Royal Institute of Technology | KTH · Department of Civil and Architectural Engineering

Despite several successful applications, structural health monitoring (SHM) of bridges is still in its exploratory phase and, despite the increase in research, many challenges remain in order for it to become a commonplace practice in civil engineering. New SHM approaches have emerged sparked by the massive amount of acquired experimental monitorin...

A machine learning approach to damage detection is presented for a bridge structural health monitoring (SHM) system. The method is validated on the renowned Z24 bridge benchmark dataset where a sensor instrumented, three-span bridge was monitored for almost a year before being deliberately damaged in a realistic and controlled way. Several damage c...

Variations in the behavior inherent to a structure can occur when the environmental (e.g. temperature) and operational (e.g. loading) conditions change. But variations in the behavior can also occur due to adverse events such as existing damage. Thus, a monitoring system that takes dynamic properties as damage-sensitive features needs foremost to c...

Variations in the behavior inherent to a structure can occur when the environmental (e.g. temperature) and operational (e.g. loading) conditions change. But variations in the behavior can also occur due to adverse events such as existing damage. Thus, a monitoring system that takes dynamic properties as damage-sensitive features needs foremost to c...

Clustering is one of the most commonly employed exploratory data analysis technique to get some valuable insight about the structure of data. It is considered to be an unsupervised learning method as there is no ground truth to compare the output of the algorithm with the true labels of the data. However, the intention in this work is not to evalua...

The method herein proposed provides a novel perspective about data processing within structural health monitoring, which is essential for automated real-time monitoring and assessment of civil engineering structures. The low- and high-frequency contents of the forced vibration response of a structure are used to train and test artificial neural net...

This paper investigates a model-free damage detection method using a laboratory model of a steel arch bridge with a five-metre span. The efficiency of the algorithm was studied for various damage cases. The structure was excited with a rolling mass and seven accelerometers were used to record its response. An artificial neural network (ANN) was tra...

Adverse situations such as prolonged downtime of a structure, unnecessary inspections, expensive allocation of personal and equipment, deficient structural performance, or failure can be avoided by using structural health monitoring (SHM). Enhanced structural safety is the leading reason for its implementation, but one of the remaining obstacles to...

This paper explores the decision making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Art...

Situations such as the collapse of civil engineering structures can be avoided if Structural Health Monitoring (SHM) systems can detect early potential failures and timely withdraw the structure from service ahead of a likely disaster. Structural safety is the leading reason for the implementation of SHM but also noteworthy is the cost reduction as...

At the same time that civil engineering structures are increasing in number, size and longevity, there is a conforming increasing preoccupation regarding the monitoring and maintenance of such structures. In this sense the demand for new reliable Structural Health Monitoring systems and damage detection techniques is high. A model-free damage detec...

Civil engineering structures continuously undergo environmental conditions changes that can lead to temporary variations of their dynamic characteristics. Therefore, damage detection techniques have to be able to distinguish abnormal changes in the response due to damage from those normally related to environmental conditions variability. This pape...

This paper presents a method that uses machine learning to detect and localize damage in railway bridges. Results of the method application to a historical bridge are presented and used to validate the proposed algorithm. For the application of this technique, both air temperature and deck accelerations data, measured under railway traffic at sever...

As civil engineering structures are growing in dimension and longevity, there is an associated increase in concern regarding the maintenance of such structures. Bridges, in particular, are critical links in today’s transportation networks and hence fundamental for the development of society. In this context, the demand for novel damage detection te...

In this study, a new, model-free damage detection method is proposed and validated on a simple numerical experiment. The proposed algorithm used vibration data (deck accelerations) and bridge weigh-in-motion data (load magnitude and position) to train a two-stage machine learning setup to classify the data into healthy or damaged. The proposed meth...

The main factors influencing the deterioration of bridges are the environmental conditions and traffic loads. Therefore, a reliable and accurate characterisation of traffic loads can improve the results from bridge rating and health bridge monitoring. In this study a bridge weigh-in-motion algorithm is developed to monitor trains passing on a steel...

In this paper the variations in dynamic properties (eigenfrequency and damping) due to seasonal effects of a single span, ballasted railway bridge are studied. It is demonstrated that both the eigenfrequency and characteristic damping vary importantly with environmental conditions and amplitude of vibration. For this, acceleration signals correspon...

In this article it is shown empirically that ballasted bridges in cold climates can exhibit a step-like variation of their natural frequencies as the yearly season changes. The bridge under study was observed to have significantly higher natural frequencies (as much as 35%) during the winter months compared to the summer. This variation was rather...

A damage detection algorithm based on Artificial Neural Network (ANN) was implemented in this study using the statistical properties of structural dynamic responses as input for the ANN. Sensitivity analysis is performed to study the feasibility of using the changes of variances and covariances of the dynamic responses of the structure as input to...

Wireless Sensor Networks (WSNs) leverage battery-powered embedded devices to sense from and act on the environment. Their characteristics are at odds with the lifetime requirements in monitoring of civil structures. In this paper, we briefly describe the challenges at stake and how to address them, drawing from recent literature and our own real-wo...