Quantitative analysis of noninvasive diagnostic procedures for induction motor drives
This paper reports quantitative analyses of spectral fault components in five noninvasive diagnostic procedures that use input electric signals to detect different types of abnormalities in induction motors. Besides the traditional one phase current spectrum analysis SC, the diagnostic procedures based on spectrum analysis of the instantaneous partial powers Pab, Pcb, total power Pabc, and the current space vector modulus csvm are considered. The aim of this comparison study is to improve the diagnosis tools for detection of electromechanical faults in electrical machines by using the best suitable diagnostic procedure knowing some motor and fault characteristics. Defining a severity factor as the increase in amplitude of the fault characteristic frequency, with respect to the healthy condition, enables us to study the sensitivity of the electrical diagnostic tools. As a result, it is shown that the relationship between the angular displacement of the current side-bands components at frequencies (ffosc) is directly related to the type of induction motor faults. It is also proved that the total instantaneous power diagnostic procedure was observed to exhibit the highest values of the detection criterion in case of mechanical faults while in case of electrical ones the most reliable diagnostic procedure is tightly related to the value of the motor power factor angle and the group motor-load inertia. Finally, simulation and experimental results show good agreement with the fault modeling theoretical results.
noninvasive diagnostic mechanical fault signature signal processing rotating machinery