Università Degli Studi Di Bologna Applications of Higher Order Spectra to the Machine Condition Monitoring

Faults occurring in machine elements are often related to non-linear effects which may lead to non-linearities in the machine vibration signature. This paper concerns the application of signal processing techniques based on Higher Order Spectra (HOS) to the condition monitoring of mechanical systems. These techniques give more information than the power spectra and are particularly useful in situations where only a single measurement sensor is available. If a process is Gaussian then HOS provide no information that cannot be obtained from the second order statistics. On the contrary, HOS give information about a signal's non-Gaussianity. Since a Gaussian input passing through a linear system leads to a Gaussian output, assuming the signal as an output of a system with a Gaussian input, then HOS make it possible to analyse the structure of the output signal and to provide information related to the non-linearity within the system. Two experimental cases are presented. The HOS are applied to detect the presence of a fatigue crack in a straight beam and to analyse the vibration signal measured on a test bench for rolling element bearings. HOS are employed to interpret the signal structure and the system's physical characteristics. Both third and fourth order spectra seem to provide a possibility of using HOS as a condition monitoring tool. 2 1 Introduction In the field of manufacturing technology, the machine condition monitoring significantly contributes to improve methods and techniques. Within condition monitoring techniques, the most established is vibration analysis which often produces satisfactory results. As a matter of fact, a link exists between machine vibrations and the health condition; moreover, transducers can be easily attached to machines and measurements are quick and efficient (Lyon, 1987). In addition, different mechanical phenomena (e.g. unbalance, gear mesh and faults, bearing faults, impacts) produce energy at different frequencies. Therefore, by signal processing techniques, diagnostic information can be obtained and the stage of the fault development can be evaluated. In particular, it can be observed that machine faults are often related to non-linearities occurring in the machine itself (e.g. fatigue crack arising in a machine components, impacts in kinematic pairs, friction). This kind of phenomena leads to non-linearities in the machine vibration signature too. This paper concerns the analysis of some mechanical systems by means of signal processing techniques based on HOS-a new area of signal processing-which has a wide variety of practical applications. HOS have been applied in fields …