Volume 1, Issue 1, 2007
An Approach of Condition Monitoring of Induction Motor Using MCSA Neelam Mehla, Ratna Dahiya
Abstract—With the industrial growth, it has become
necessary to monitor the condition of the machine/system. Electrical machine being the most sensitive part has great importance for the researcher to monitor the faults diagnosis. Three phase squirrel cage motor is normally use for industrial purposes. Various techniques are used to control the speed such as DTC (Direct Torque Control), Vector Control, Close Loop Feedback Control etc. Small single phase Induction machine are used for home appliances hence the machine monitoring plays an important role for industrial as well as domestic appliances growth. Various fault detection method has been used in past two decades. Special attention is given to non-invasive methods which are capable to detect fault using major data without disassembly the machine. The Motor Current Signature Analysis (MCSA) is considered the most popular fault detection method now a day because it can easily detect the common machine fault such as turn to turn short ckt, cracked /broken rotor bars, bearing deterioration etc. The present paper discusses the fundamentals of Motor Current Signature Analysis (MCSA) plus condition monitoring of the induction motor using MCSA.
he operators of induction motor drives are under continual pressure to reduce maintenance costs and prevent unscheduled downtimes that result in lost production and financial income. Many operators now use online condition-based maintenance strategies in parallel with conventional planned maintenance schemes. However, it is still the operator who has to make the final decision on whether to remove a motor from service or let it run based on information from condition monitoring systems. A crucial point about motor current signature analysis (MCSA) is that it is sensing an electrical signal that contains current components that are a direct by-product of unique rotating flux components caused by faults such as broken rotor bars, air gap eccentricity, and shorted turns
in low voltage stator windings, etc. MCSA can detect these problems at an early stage and thus avoid secondary damage and complete failure of the motor [2, 4, 7, and 6]. It is true that broken rotor bars will result in a change to the vibration spectrum, but vibration is traditionally sensed at the bearings. And for each motor there is a different mechanical stiffness between the electromagnetic forces caused by broken bars and the position where the vibration is sensed. This adds an additional complexity when attempts are made to quantify the severity of the problem via vibration analysis. Electromagnetic forces are proportional to the flux density squared waveform in an induction motor [6, 7]. Hence, the vibration from unique electromagnetic forces from broken bars, etc., is a second order effect compared to current components directly induced from the specific rotating flux waves. In many cases, the fault severity (e.g., number of broken rotor bars) has to be serious before it can be detected by vibration analysis, and even then the prediction of fault severity is another order of magnitude more difficult. This is not the case with MCSA as has been proven via numerous industrial case histories. With respect to detecting airgap eccentricity problems, a similar reasoning applies as reported by Cameron, et al. , Tavner and Penman , and as demonstrated via industrial case histories by Thomson and Barbour,  and Thomson, et al. . With respect to detecting shorted turns in low voltage stator windings then Thomson  has shown that MCSA can detect the fault before a phaseto-phase or phase-to-earth failure. It is therefore possible with a low voltage (LV) stator winding to have some lead time between shorted turns.