Generalized singular value decomposition in multidimensional condition monitoring of machines—A proposal of comparative diagnostics

With the modern metrology, we can measure almost all variables in the phenomenon field of working machine, and many of measuring quantities can be symptoms of machine condition. On this basis, we can form the symptom observation matrix (SOM) for condition monitoring. From the other side we know that contemporary complex machines may have many modes of failure, so-called faults, which form the fault space. Even if we apply some modern tool like singular value decomposition (SVD) for the fault extraction purpose, this multidimensional problem is not a simple one. Therefore, the question remains if one can learn considering similar problem when having SOM of similar machine observed just before. In this way, we can consider the application of generalized singular value decomposition (GSVD) to the machine condition monitoring problems, and uncover some new possibilities.