Review of Vibration Based Fault Diagnosis in Rolling Element Bearing and Vibration Analysis Techniques

Transcription

1 998 Review of Vibration Based Fault Diagnosis in Rolling Element Bearing and Vibration Analysis Techniques Ragini Sidar 1, Prakash Kumar Sen 2, Gopal Sahu 3 1 Student, Mechanical Engineering, Kirodimal Institute of Technology, Raigarh (C.G.) 2,3 Lecturer, Mechanical Engineering, Kirodimal Institute of Technology, Raigarh (C.G.) ABSTRACT Rolling element bearings are one of the major machinery components used in industries like power plants, chemical plants and automotive industries that require precise and efficient performance. Vibration monitoring and analysis is useful tool in the field of predictive maintenance. Health of rolling element bearings can be easily identified using vibration monitoring because vibration signature reveals important information about the fault development within them. Numbers of vibration analysis techniques are being used to diagnosis of rolling element bearings faults. This paper attempts to summarize the recent research and developments in rolling bearing vibration analysis techniques. Bearing defects and bearing characteristic frequencies (BCF) are also discussed. Keywords Rolling Element Bearing, Vibration, Bearing Fault, Vibration Analysis, Fault Diagnosis. 1. INTRODUCTION Rolling element bearings are at the heart of almost every rotating machine. Therefore, they have received a lot of attention in the field of vibration analysis as they represent a common source of faults (1). In order to keep machinery operating at its best and avoid catastrophic failure, financial cost and personal injuries, different methods bearing fault diagnosis have been developed and used effectively to detect the machine faults at an early stages, among which vibration signal processing is the most frequently applied one.(2) Vibration based condition monitoring have been widely used for detection and diagnosis of bearing defects for several decades.(3) Bearing failures can sometimes cause both personal damage and economic loss, if the fault cannot be detected and diagnosed well in advance. Proper functioning of these appliances depends, to a great extent, on the smooth and quiet running of the bearings [3]. Material fatigue, faulty, installation, or inappropriate lubrication may cause localized defects of rolling bearings. Each time the rolling element passes over the defect, an impulse of vibration is generated [4]. Different methods are used for detection and diagnosis of bearing defects; they may be broadly classified as vibration and acoustic measurements, temperature measurements and wear debris analysis. Among these, vibration measurements are the most widely used. Several techniques have been applied to measure the vibration and acoustic responses from defective bearings; i.e., vibration measurements in time and frequency domains, the shock pulse method, sound pressure and sound intensity techniques and the acoustic emission method [3]. Well performance and reliability of rolling element bearings is essential for proper functioning of machines and to prevent catastrophic failure of the machinery. Bearing health and performance can be easily identified by using health monitoring techniques. Many condition monitoring techniques is available to monitor the health of bearing; these are wear debris analysis, motor current analysis, noise monitoring, temperature monitoring, vibration monitoring etc. But the vibration monitoring is the most useful technique because it is reliable and very sensitive to fault severity. Bearings act as a source of vibration and noise because of either varying compliance or the defects presence in parts of bearing. These vibration signals will give us information about the health of bearing. Vibration monitoring is the most popular technique to diagnosis of rolling element bearing faults. Many researchers have been worked on vibration signal analysis techniques and numbers of research papers have been published by them. Review papers have also been published by researchers on bearing defects diagnosis techniques. In 1983, Kim and Lowe [5] the aim of this study is to include the recent research and developments in the vibration analysis techniques for diagnosis of rolling element bearings faults.

2 ROLLING ELEMENT BEARING COMPONENTS AND GEOMETRY Bearing geometry is a critical factor for diagnosing bearing defects because the geometry of ball bearings determines the dynamics of the bearing components and their vibration characteristics. Figure 2.1 shows a typical deep groove ball bearing and figure 2.2 shows components, applied force, load zone and load distribution. Ball bearings have smaller sizes and limited load carrying capacity compared to the other rolling element bearings, but they can support both axial and radial loads. Axial force is defined as the force applied parallel to the shaft whereas the radial force is applied perpendicular to the shaft. Correct alignment, placement where it is used, enough lubrication are the important points to take care of to maximize the life-span of this equipment [6]. A ball bearing consists of an inner race, an outer race, balls, a cage holding the balls apart from each other and a shaft. The load zone and load distribution are also given with the direction of applied force in the figure. In most cases, the outer race is held stationary where the inner race and the balls rotate. Most of the defects on the inner side of outer race such as cracks or pits occur on the locations subject to the load zone, since they are directly under the applied force. Figure 2.1: Typical deep-groove ball bearing [6] 3. CHARACTERISTIC FREQUENCIES OF BEARING FAULTS Rolling element bearing consists of an inner race, an outer race, rolling elements and a cage, which holds the rolling elements in a given relative position, as presented in Fig.1. In order to find the characteristics of the vibration responses due to faults, the bearing rings are assumed to be isolated continuous systems. It is further assumed that: (1) All rollers are equal in diameter; (2) There is in pure rolling contact between rollers, inner race and outer race; (3) There is no slipping between the shaft and the bearing; (4) Outer race is stationary and inner race rotates. The relative velocity between rollers, inner race and outer race are zero because they are in pure rolling contact. Race surface fatigue results in the appearance of spalls on the inner race, outer race or rolling elements. If one of the races has a spall, it will almost periodically impact with rolling elements. The fault signature is represented by successive impulses with a repetition rate depending on the faulty component, geometric dimensions and the rotational speed. The period between impacts is different for all the listed elements and depends on the geometry of the bearing, the rotational speed and the load angle. For a fixed outer race bearing, the theoretical characteristic fault frequencies can be calculated using Eq. (1)-(4), and a derivation of these equations is presented in (7). 1 Fundamental cage frequency fc = 1 Dr fs(1 cos )..(1) 2 Dc 2 Outer race defect frequency Figure 2.2: Ball bearing components, applied force, load zone and load distribution [6]. f0 = Nr 2 Dr fs 1 cos (2) Dc 3 Inner race defect frequency

3 1000 fi = Nr 2 Dr fs(1 + cos ) (3) Dc 4 Roller defect frequency fr = Dc.fc 2Dr (1 Dr 2 Dc 2 cos2 )..(4) where, Dc is pitch circle diameter, Dr is roller diameter, is contact angle, Nr is number of roller and Fs is shaft rotational frequency. 4. BEARING DEFECTS The defects in the rolling element bearings may arise mainly due to following reasons such as; improper design of the bearing or improper manufacturing or mounting, misalignment of bearing races, unequal diameter of rolling elements, improper lubrication, overloading, fatigue, uneven wear etc. The rolling element bearing defects/faults classified into two categories; distributed defects and localized defects. A. Distributed Defects Distributed defects are mainly caused by manufacturing error, inadequate installation or mounting and abrasive wear [8]. Distributed defects include surface roughness, waviness, misaligned races and unequal diameter of rolling elements [9]. The change in contact force between roiling elements and raceways due to distributed defects cause an increased in the vibration level. Hence, the study of vibrations generated by distributed defects is mainly for quality inspection of bearings as well as for condition monitoring [10]. Fig.4.1 Defective Bearing with 1mm defect on outer race B. Localized Defects These defects include cracks, pits and spalls on rolling surfaces caused by fatigue [11]. The common failure mechanism is the crack of the races or rolling elements, mainly caused when a crack due to fatigue originated below the metal surface and propagated towards the surface until a metal piece is detached causing a small defect or spall [3]. This defect accelerate when the bearing is overloaded or subjected to shock (impact) loads during their functioning and also increase with the rotational speed. Spalling can occur on the inner ring, outer ring, or rolling elements. 5. BEARING FAILURE MODES The normal service life of a rolling element bearing rotating under load is determined by material fatigue and wear at the running surfaces. Premature bearing failures can be caused by a large number of factors, the most common of which are fatigue, wear, plastic deformation, corrosion, brineiling, poor lubrication, faulty installation and incorrect design. Common modes of bearing failure are discussed below [12]: A. Fatigue Fatigue damage begins with the formation of minute cracks below the bearing surface. As loading continues, the cracks progress to the surface where they cause material to break loose in the contact areas. The actual failure can manifest itself as pitting, spalling or flaking of the bearing races or rolling elements. If the bearing continues in service, the damage will spread in the locality of the defect is due to stress concentration [12]. B. Wear Wear is another common cause of bearing failure. It is caused mainly by dirt and foreign particles entering the bearing through inadequate sealing or due to contaminated lubricant. The abrasive foreign particles roughen the contacting surfaces giving a dull appearance. Severe wear changes the raceway profile and alters the rolling element profile and diameter, increasing the bearing clearance. The rolling friction increases considerably and can lead to high levels of slip and skidding, the end result of which is complete breakdown [12].

4 1001 C. Plastic deformation Plastic deformation of bearing contacting surfaces can be the result of a bearing subject to excessive loading while stationary or undergoing small movements. The result is indentation of the raceway as the excessive loading causes localized plastic deformation. In operation, the deformed bearing would rotate very unevenly producing excessive vibration and would not be fit for further service [12]. D. Corrosion Corrosion damage occurs when water, acids or other contaminants in the oil enter the bearing arrangement. This can be caused by damaged seals, acidic lubricants or condensation which occurs when bearings are suddenly cooled from a higher operating temperature in very humid air. The result is rust on the running surfaces which produces uneven and noisy operation as the rust particles interfere with the lubrication and smooth rolling action of the rolling elements [12]. E. Brinelling Brinelling manifests itself as regularly spaced indentations distributed over the entire raceway circumference, corresponding approximately in shape to the Hertzian contact area. Three possible causes of brinelling are, (1) Static overloading which leads to plastic deformation of the raceways, (2) When a stationary rolling bearing is subject to vibration and shock loads and (3) When a bearing forms the loop for the passage of electric current [12]. F. Lubrication Inadequate lubrication is one of the common causes of premature bearing failure as it leads to skidding, slip, increased friction, heat generation and sticking. At the highly stressed region of Hertzian contact, when there is insufficient lubricant, the contacting surfaces will weld together, only to be torn apart as the rolling element moves on. The three critical points of bearing lubrication occur at the cageroller interface, the roller-race interface and the cage race interface [12]. G. Faulty installation Faulty installation can include such effects as excessive preloading in either radial or axial directions, misalignment, loose fits or damage due to excessive force used in mounting the bearing components [12]. H. Incorrect design Incorrect design can involve poor choice of bearing type or size for the required operation, or inadequate support by the mating parts. Incorrect bearing selection can result in any number of problems depending on whether it includes low load carrying capability or low speed rating. The end result will be reduced fatigue life and premature failure [12]. 6. VIBRATION ANALYSIS TECHNIQUES There is several vibration analysis techniques used to analyses the bearing vibration. In this paper, vibration analysis techniques are classified in four categories: time domain, frequency domain, timefrequency domain and other techniques. A. Time Domain Techniques Time domain technique is easiest and simplest technique to analyze the vibration signal waveform. Peak-to-peak amplitude is measure from the top of the positive peak to the bottom of the negative peak. Root mean square (RMS), measures the overall level of a discrete signal. RMS (X) = xi 2 N.(5) Where, N is the number of discrete points and represents the signal from each sampled point. The resultant RMS values are compared with recommended values to determine the condition of a bearing [13]; however, this method is not sensitive to detect small or early-stage defects [14]. B. Frequency Domain Techniques Frequency domain, or spectral analysis, is the most popular approach for the diagnosis of bearing faults. Frequency-domain techniques convert timedomain vibration signals into discrete frequency components using a fast Fourier transform (FFT). Simply stated, FFT mathematically converts timedomain vibration signals trace into a series of discrete frequency components. The Fast Fourier Transform (FFT) is an algorithm for calculation of the Desecrate Fourier Transform first published in 1965 by J.W.Cooley and J.W.Tuckey [15].In a frequency

5 1002 spectrum plot, the X-axis is frequency and the Y-axis is the amplitude of displacement, velocity, or acceleration. The main advantage of frequency-domain analysis over time-domain analysis is that it has ability to easily detect the certain frequency components of interest. James Taylor. C. Time-Frequency Domain Techniques Time-frequency domain techniques have capability to handle both, stationary and nonstationary vibration signals. This is the main advantage over frequency domain techniques. Time frequency analysis can show the signal frequency components, reveals their time variant features. A number of timefrequency analysis methods, such as the Short-Time Fourier Transform (STFT), Wigner-Ville Distribution (WVD), and Wavelet Transform (WT), have been introduced. STFT method is used to diagnosis of rolling element bearing faults [17]. The basic idea of the STFT is to divide the initial signal into segments with short-time window and then apply the Fourier transform to each time segment to ascertain the frequencies that existed in that segment. The advantage of wavelet transform (WT) over the STFT is that it can achieve high frequency resolutions with sharper time resolutions. An enhanced Kurtogram method used to diagnosis of rolling element bearing faults by Wang et al. [18]. D. Other Techniques Many other techniques have been used to diagnosis of rolling element bearing faults e.g. artificial neural networks (ANNs), fuzzy logic systems etc. Baillie and Mathew [19] proposed the application of ANNs to diagnosis of rolling element bearing faults. The main advantage of this time domain based model that can detect faults using short data length. Liu etal. [20] have developed a fuzzy expert system for rolling element bearing fault diagnosis. Jack et al. [21] used radial basis function (RBF) networks for diagnosis of rolling element bearing faults but this network is fail to classify outer race and cage defects. Feed forward neural network (FFNN) structure is the mostly used neural network structure in the diagnosis of machine faults [22]. 7. CONCLUSION In review paper for fault detection technique in rolling element bearing, Vibration measurement in time domain and frequency domain are key points for doing work. So, we will use time domain and frequency domain for feature extraction and fault diagnosis in our work.[23] This study found that the time domain techniques only can indicate the fault(s) present in the bearing but it can t identify the location. Frequency domain techniques have ability to identify the location of fault(s) in bearing. Vibration peaks generates in spectrum at the bearing characteristics frequencies, from that we can easily understand which bearing element is defected. Envelope analysis is very useful method to detect incipient failure of rolling element bearing. REFERENCES [1]. McFadden, P. and J. Smith, Model for the vibration produced by a single point defect in a rolling element bearing. Journal of Sound and Vibration, (1): p [2]. Lei, Y., Z. He, and Y. Zi, A new approach to intelligent fault diagnosis of rotating machinery. Expert Systems with Applications, (4): p [3]. Tandon, N. and A. Choudhury, A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International, (8): p [4]. L. Zhen, H. Zhengjia, Z. Yanyang, and W. Yanxue, "Customized wavelet denoising using intraand inter-scale dependency for bearing fault detection," Journal of Sound and Vibration, vol. 313, pp , [5]. P.Y. Kim and I.R.G. Lowe, A review of rolling element bearing health monitoring. In: Proceedings of Machinery Vibration Monitoring and Analysis Meeting Vibration Institute, Houston, TX, pp , April, [6]. Aziz Kubilay Ovacikli, Condition Monitoring of Ball Bearings Using Vibration Analysis, Master s Thesis, Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology [7]. Tomasz Barszcz and Nader Sawalhi, Fault Detection Enhancement in Rolling Element Bearings Using the Minimum Entropy Deconvolution, Archives ofacoustics, vol. 37, 2012, pp

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