This paper concerns the health monitoring of pipelines and tubes. It proposes the k-means clustering algorithm as a simple tool to monitor the integrity of a structure (i.e., detecting defects and assessing their growth). The k-means algorithm is applied on data collected experimentally, by means of an ultrasonic guided waves technique, from healthy and damaged tubes. Damage was created by attaching magnets to a tube. The number of magnets was increased progressively to simulate an increase in the size of the defect and also, a change in its shape. To test the performance of the proposed method for damage detection, a statistical population was created for the healthy state and for each damage step. This was done by adding white Gaussian noise to each acquired signal. To optimize the number of clusters, many algorithms were run, and their results were compared. Then, a semi-supervised based method was proposed to determine an alarm threshold, triggered when a defect becomes critical.

By analyzing the arrival times of guided waves, the acoustic source in a plate is predicted. Solving this problem is important for continuous health monitoring of structures. Several techniques based on the triangulation principle have been proposed for this purpose but they do not work for anisotropic plates. The popular triangulation technique assumes that the wave velocity is the same in all directions, which is not true for anisotropic plates. An alternative method based on the optimization scheme was proposed by Kundu et al. (Kundu T, Das S and Jata KV. Point of impact prediction in isotropic and anisotropic plates from the acoustic emission data.

This paper deals with the health monitoring of rails. Many nondestructive techniques have been applied to rule on the health of rails. Ultrasonic guided waves (UGWs) technique is one among them. The current study focuses on this technique. First, it describes several kinds of defects that can occur in rails. Then, it presents the principle, advantages and limitations of UGW technique. The paper gathers as exhaustive as possible the previous works in which the said technique was used as a tool to monitor the health of rails. The paper put special emphasis on the use of UGW in structural health monitoring (SHM) context. In order to better understand the benefit/need of this technique in this context, by especially the non-specialist reader, a background concerning SHM is provided.