Automatic anomaly detection and processing for long-term tension monitoring of stay cables based on vibration measurements

Abstract

Abstract Stay cables are the crucial force-transmitting components of cable-stayed bridges. Consequently, effective cable tension monitoring is typically regarded as the most important issue in structural health monitoring for this type of bridge. In the long-term monitoring of structures, the occurrence of abnormal signals due to a variety of reasons such as sensor faults, a system malfunction, data loss in transmission, or the instability of power supply, are almost unavoidable and are highly likely to lead to a deterioration in the quality of subsequent analyses. The current paper presents the first phase of a project to develop an automatic monitoring system for cable tension based on ambient vibration signals for the Mao-Luo-Hsi Bridge. The results demonstrate that automatic anomaly detection and processing for cable vibration measurements can be achieved with a relatively simple algorithm using an appropriate threshold of maximum response value. In addition, the paper also reports the elimination of anomalies during testing of the monitoring system installation.