Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

The J1030 field: a new window on early large scale structures and faint radio-galaxy populations

The correlations between the evolution of the Super Massive Black Holes (SMBHs) and their host galaxies suggests that the SMBH accretion on sub-pc scales (active galactice nuclei, AGN) is linked to the building of the galaxy over kpc scales, through the so called AGN feedback. Most of the galaxy assembly occurs in overdense large scale structures (LSSs). AGN residing in powerful sources in LSSs, such as the proto-brightest cluster galaxies (BCGs), can affect the evolution of the surrounding intra-cluster medium (ICM) and nearby galaxies. Among distant AGN, high-redshift radio-galaxies (HzRGs) are found to be excellent BCG progenitor candidates. In this Thesis we analyze novel interferometric observations of the so-called "J1030" field centered around the z = 6.3 SDSS Quasar J1030+0524, carried out with the Atacama large (sub-)millimetre array (ALMA) and the Jansky very large array (JVLA). This field host a LSS assembling around a powerful HzRG at z = 1.7 that shows evidence of positive AGN feedback in heating the surrounding ICM and promoting star-formation in multiple galaxies at hundreds kpc distances. We report the detection of gas-rich members of the LSS, including the HzRG. We showed that the LSS is going to evolve into a local massive cluster and the HzRG is the proto-BCG. we unveiled signatures of the proto-BCG's interaction with the surrounding ICM, strengthening the positive AGN feedback scenario. From the JVLA observations of the "J1030" we extracted one of the deepest extra-galactic radio surveys to date (~12.5 uJy at 5 sigma). Exploiting the synergy with the X-ray deep survey (~500 ks) we investigated the relation of the X-ray/radio emission of a X-ray-selected sample, unveiling that the radio emission is powered by different processes (star-formation and AGN), and that AGN-driven sample is mostly composed by radio-quiet objects that display a significant X-ray/radio correlation.