Bearing Faults Condition Monitoring – A Literature Survey HARLIŞCA Ciprian, SZABÓ Loránd Department of Electrical Machines and Drives, Technical University of Cluj-Napoca 400114 Cluj-Napoca, Memorandumului 28, Romania; e-mail: Ciprian.Harlisca@mae.utcluj.ro Abstract – Bearing related faults are one of the most common causes of failure in electrical machines. By means of advanced diagnosis methods it is possible to detect these faults in their incipient phase, before the catastrophic effects of the failures can occur. The aim of this paper is to make a brief survey of the condition monitoring techniques used in the field of bearing fault diagnosis. Keywords : bearing faults, diagnosis, induction machines, fault detection, condition monitoring. I. INTRODUCTION In most industrial processes unplanned stops due to failures have a high economic impact on the cost of the process and it may result in significant process down time. The fault can occur in any part of the machine or even in the drive system. The faults of electrical machine could be electrical or mechanical. The main electrical faults are the stator and rotor windings (or cage) faults [1], [2]. Mechanical faults include bearing faults, air-gap eccentricity, misalignment, gearboxes faults, etc. The research on fault diagnosis has shown that the most of the failures of induction machines (about 40%) are related to the bearings [3]. The bearing related faults do not cause immediate breakdown, they evolve in time until they produce a critical failure of the machine. Unfortunately these failures results both in costly repair and downtime. The bearings faults can be caused by material fatigue, overheating, harsh environments, inadequate storage, contamination, corrosion, wrong handling and installation, etc. But the main cause of their failure is due to poor lubrication, which can be easily avoided by a correct maintenance plan. Vibration based monitoring techniques are usually applied for the diagnosis of the bearings. Unfortunately these methods require vibration sensors and special equipment for the condition monitoring. They also need access to the machine under testing, which is not always possible. Compared to the methods above, the current monitoring requires only (frequently already existing) simple and cheap current sensors. The current monitoring based techniques can be used to detect a large number of faults: broken rotor bars [4] [5], shorted windings, air-gap eccentricity [6], bearing faults [7], load faults, etc. These methods are non-intrusive and can be applied both on-line and in a remotely controlled way. II. BEARING FAULTS A rolling-element bearing is generally composed of two rings, between which a set of balls or rollers rotate in raceways. In most cases, bearing failures are the result of material fatigue of the bearing. Under normal operating conditions fatigue failure begins with small cracks, located inside the surfaces of the raceway and rolling elements. The repetitive impacts between the components of the bearing and the faulted surfaces cause the cracks to gradually propagate and expand, generating an increase in vibrations and noise levels [8]. The repetitive stressing of the damaged area causes the detachment of some small fragments of the material, which produce a phenomenon known as flaking or spalling [9] The pattern of the vibration signal consists in a succession of oscillations which repeat with each pass of a moving component over the fault [10]. The repetition frequency of the impact depends on the position of the fault. The fault can be on the inner race, the outer race or on the rolling element The typical construction and sizes of a ball bearing is shown in Fig. 1. The balls are fixed and held together by a cage which prevents the contact between the balls and ensures a uniform distance between them. Figure 1. Main bearing dimensions and characteristic fault frequencies [1]. In the literature the bearing faults are classified according to: __________________________________________________________________________________________________________ Journal of Computer Science and Control Systems 19