DETECTION AND LOCALISATION OF DAMAGE ON INDUSTRIALLY PRODUCED CONCRETE SLABS THROUGH TIME- AND FREQUENCY-DOMAIN APPROACHES

in Carrera, E.; Miglioretti, F; Petrolo, M. (Eds.) 6th ECCOMAS Thematic Conference on Smart Structures and Materials (SMART2013), Torino 24-26 June 2013 (2013, June)

The objective of this work is to address the problem of damage detection in civil engineering structures using non-destructive techniques and dynamic measurements. To this purpose, time- or frequency ... [more ▼]

The objective of this work is to address the problem of damage detection in civil engineering structures using non-destructive techniques and dynamic measurements. To this purpose, time- or frequency-domain methods are used for the diagnostics. It consists in practical output-only techniques as Stochastic Subspace Identification (SSI) for modal identification or Enhanced Principal Component Analysis (EPCA) for detecting the presence of damage. The use of the Hankel matrix instead of the observation matrix improves effectively the robustness of these methods. Damage localization is based on Frequency Response Functions (FRFs) and sensitivity analysis of PCA results. The efficiency of the above-mentioned methods has been demonstrated in earlier studies mainly on numerical examples and small-scale laboratory experiments. It was also tested successfully on industrial examples to perform machine condition monitoring using a reduced set of sensors. In this work, the investigation is performed on precast prestressed and non-prestressed concrete slabs. Successive damages were artificially introduced in the slabs by loading heavy weights and by cutting steel wires, which induced cracks in the structure. The examples show the consequences of the considered techniques for damage identification. The results that are very different between prestressed and non-prestressed slabs may be used as input for the condition control of this kind of structures. [less ▲]

Fault Diagnosis in Industrial Systems Based on Blind Source Separation Techniques Using One Single Vibration Sensor

in Shock and Vibration (2012), 19(5), 795-801

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In ... [more ▼]

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In machine condition monitoring, the number of available vibration sensors is often small and it is not unusual that only one single sensor is used to monitor a machine. The aim of this paper is to propose an extension of fault detection techniques that may be used when a reduced set of sensors or even one single sensor is available. Fault detection techniques considered here are based on output-only methods coming from the Blind Source Separation (BSS) family, namely Principal Component Analysis (PCA) and Second Order Blind Identification (SOBI). The advantages of PCA or SOBI rely on their rapidity of use and their reliability. Based on these methods, subspace identification may be performed by using the concept of block Hankel matrices which make possible the use of only one single measurement signal. Thus, the problem of fault detection in mechanical systems can be solved by using subspaces built from active principal components or modal vectors. It consists in comparing subspace features between the reference (undamaged) state and a current state. The angular coherence between subspaces is a good indicator of a dynamic change in the system due to the occurrence of faults or damages. The robustness of the methods is illustrated on industrial examples. [less ▲]