wear characterisation of connecting rod bore bearing … · wear characterisation of connecting rod...

Wear Characterisation of Connecting Rod Bore Bearing Shell Using I-kaz and Taylor Tool Life Curve Methods

M. J. GHAZALI, M. Z. NUAWI, N. I. I. MANSOR, F. LAMIN

Department of Mechanical and Materials Engineering Universiti Kebangsaan Malaysia

43600, Bangi, Selangor, Malaysia

Abstract: - This paper presents a simple method for detecting of wear bearing progression that ranged of low frequency signal f < 20 kHz. This new statistical approached can be computed in real time. The implementation of this technique gives pattern recognition in order to identify bearing wear. The wear test was conducted under pin-on-disc configuration in lubricated sliding condition. It was found that the higher value of I-kaz coefficient, Z∞ was represented by scattered data in three dimensional in I-kaz three dimensional big spaces and vice versa. It was found that the results for this method may capture realistic behaviour of bearing contacts in which correlates wear progression and the produced signal. From the statistical analyses of the wear bearing, it was possible to correlate the relationship between Taylor Tool Life curve, which was utilized in identifying typical wear growth. The Z∞ and Taylor curve were observed to the trend of wear rate. The lower value of Z∞ indicating wear became severe as showed in failure region in Taylor curve. Key-Words: - Bearing wear, I-kaz, Taylor curve, Wear monitoring. 1 Introduction Bearings are one of the most important and frequently encountered elements in motor systems which play an important role in the proper operation of these systems. Bearings used for supporting the rotating part of engine, are one of the crucial elements by which the safe operation of the engine is ensured. Wear mechanism is expected to take place because of load and speed combination and also due to degradation or lack of lubricant in the interface region conducting a metallic contact between bearing and shaft surfaces. As a result, monitoring condition of bearing has been a subject of extensive research for the last 25 years [1,2]. Studies on bearing acoustical properties could provide significant qualitative information that correlates to the measured values. A measured signal is commonly consist of variation of amplitude, frequency, phase and energy. There have been a variety of analysis method exist for condition monitoring of bearings including vibration analysis, oil analysis, infrared thermography and motor current signature analysis [1]. Investigation on the statistical parameters derived from the time domain signals is the simplest vibration analysis technique. It has been studied that vibration signals from good and defective bearings manifest statistically different behaviours in the time domain, such as different peak,

root-mean square (rms), crest factor, kurtosis, skewness values and cyclic spectral analysis [3,4]. By collecting data from samples at various points within the process, variations in the process that may affect the quality of the end product or service can be detected and corrected, thus reducing waste as well. The statistical methods that summarise a collection numerically or graphically data is called descriptive statistics while the inferential statistics model is the pattern data that permits randomness and uncertainty in the observations. The I-kaz method was developed on both descriptive and inferential statistics, which numerical descriptor of I-kaz is the I-kaz coefficient, Z∞ and the value of the coefficient is supported by three dimensional graphical summarisations of frequency distribution [5,6]. The I-kaz method was introduced based on the concept of frequency distribution about its centroid. Simultaneously, the I-kaz coefficient, Z∞ can be written as in Eq. (1) which can be used to measure the space of scattering.

Z∞( ) ( ) ( )

21

4

21

4

21

4

N

x

N

x

N

xN

iV

VN

iH

HN

iL

Liii ∑∑∑

===

−+

−+

−=

μμμ (1)

where xi

L, xi,H

xiV are the value of discrete data in low

frequency (LF), high frequency (HF) and very high

Proceedings of the 1st WSEAS International Conference on MATERIALS SCIENCE (MATERIALS'08)

ISSN: 1790-2769 110 ISBN: 978-960-474-024-6

frequency range respectively (VF) at the i-sampel of time, μL, μH and μV are mean of each frequency band and N is the number of data. Tool life is known as the time for tools that can be reliably be used for cutting before it must be discarded or repaired. A tool life equation was developed by Taylor [7] as shown in Eq. (2). In this paper, new technique of signal analysis-based tool wear monitoring method [6] for bearing alloy is presented. The parameters value is taken by considering the volume loss at various times.

VTn = C (2)

where V=cutting speed, m/min, T = tool life and n and c are parameters which values depend on feed, depth of cut, work material, tooling and tool life criterion used. The focus of the present paper is to investigate the wear of deformed bearing under lubricated condition via air-borne method. To do this, the patterns of frequencies can be recognized and changes in this pattern can be identified the moment bearing starts to wear or deform. Table 1 Experimental condition of the wear test

2 Methodology Wear tests were performed using a computer-controlled pin-on-disc machine, (DUCOM TR281-M), which produces a linear relative oscillating motion. Table 1 shows the experimental conditions of the wear test. The wear test of commercial bearing alloy against hardened AISI 4340 steels was carried out in lubricated condition at room temperature with sliding distance ranging from 500 m to 2400 m. The type of lubricants used was Elf (15W/50) multigrade oil. All bearings were kept constant at a surface roughness of 0.02 µm prior to the test with the density of bearing 6.98 g/cm3. Lancaster wear coefficient, K’ [8] was utilized according to Eq. (3), where V = volume loss (mm3), FN = normal load (N) and L = sliding distance. A detailed observation on worn surfaces was carried out using SEM (Hitachi TM-1000)

Wear coefficient, K’ = V (mm3) (2)

FNL (N/m) All the results presented were obtained with the CCP Probe Microphone Type 40SC located 10 mm to the pin bearing, with frequency-response ranging from 2 Hz up to 20 kHz (fmax). Signals were fed into a data acquisition system on a PC and were sampled at 50 kHz. All the real-time signal data are then transferred to MATLAB. The effectiveness of I-kaz method was determined by observing the ability of I-kaz display and I-kaz coefficient, Z∞. The time domain signal is decomposed into three frequency ranges, which are x-axis: low frequency (LF) range 0-0.25 fmax, y-axis: high frequency (HF) range of 0.25 fmax-o.5 fmax and z-axis: very high frequency (VF) ranges of 0.5 fmax [5]. The selection of 0.25 fmax and the 0.5 fmax as low and high frequency limit respectively imply the concept of a 2nd order Daubechies [9] in signal decomposition process. 3 Results and Discussions Table 2 represents the wear results of the bearing shell against hardened AISI 4340 steels. Fig. 1 shows the wear coefficient, K’ as a function of sliding distance. The wear coefficient, K’ was obtained from a volume loss ranging between 4.4x10-5 to 8.5x10-5 mm3/Nm. Using a curve fitting method, the K’ = 0.02755 /(L) + 2.673x10-5, where L is sliding distance. From the results, it is suggested that the wear was classified under a moderate wear [10]. A moderate wear normally occurs with less compatible or with well-lubricated surfaces, and it occurs more readily when the pressure at the interface between the sliding surfaces is low. For metal-on metal lubricated sliding system, a moderate wear coefficient is around l0-4 - 10-6 [10]. Bearings with a sliding distance of 500 m showed the highest wear coefficient (8.5x10-5 mm3/Nm) while an increased in the sliding distance significantly reduce the wear rates to approximately 4.4x10-5 mm3/Nm and finally became constant after sliding for 2400 m. This was also in agreement with Yang [11] who stated that the higher initial running-in wear rates, the higher value of K’ which eventually reached a steady state value when the wear rate becomes constant. As shown in Fig. 2 the equation of I-kaz coefficient, Z∞ is 7.36x10-10 /(L) + 5.11x10-12. It was found that the equation for K’ and Z∞ are similar with general equation y = a/(L) + c. In other word, Z∞ behaves in the same manner as the K’ otherwise it can be concluded that Z∞ ≈ K’.

Bearing condition after lubricated sliding was verified accordingly using I-kaz method. The space scattering of I-kaz representation was measured by Z∞

value obtained from Eq. (1). Obviously, the space

Pin diameter (mm) 10

Load (N) 30

Sliding speed 239rpm (0.25m/s)

Wear track diameter (mm) 20

Sliding distance, L (m) 500,800,1200

Temperature (°C) 24-29

Sliding condition Oil lubrication


ISSN: 1790-2769 111 ISBN: 978-960-474-024-6

scattering of the signal data distribution in I-kaz representation tend to shrink from 8.35x10-12 to 3.05x10-

12 as shown in Fig. 3. It was found that, when the wear became severe the distribution of data will be concentrated into smaller space volume. It can be concluded that the higher value of Z∞ represents bigger space scattering whereas small value of Z∞ represents small space scattering respectively.

500 1000 1500 2000

4

5

6

7

8

x 10-5

Sliding distance, L (m)

Wea

r coe

ffic

ient

, K' (

mm

3/N

m)

400 600 800 1000 1200 1400 1600 1800 20005.5

6

6.5

7

7.5

8

8.5

x 10-12

Sliding distance, L (m)

I-ka

z co

effic

ient

Table 2: Relationship between I-kaz coefficient, Z∞and wear coefficient, K’.

K’ = 0.02755 /(L) + 2.673x10-5

FIGURE 1 Wear coefficient, K’ as a function of sliding distance.

Z∞ = 7.36x10-10 /(L) + 5.11x10-12

FIGURE 2 I-kaz coefficient, Z∞ as a function of sliding distance.

5

x 10 -4

0

-5

(a) 15 min

(b) 75 min

00.2

0.40.6

0.81

x 10-3

-5

0

5

10

x 10-4

-10

-5

0

5

x 10-4

LFHF

VF

(c) 150 min

FIGURE 3 The I-kaz display for bearing wear at (a) I-kaz coefficient, Z∞= 8.35x10-12 (b) Z∞ = 6.5594x10-12(c) Z∞ = 3.05x10-12

Sliding distance,L (m)

I-kaz coefficient, Z∞

Wear coefficient, K’ (mm3/Nm)

500 8.35x10-12 8.50x10-5

800 6.3835x10-12 5.79 x10-5

1200 5.6035x10-12 4.42 x0-5

2400 5.4935x10-12 4.38 x10-5

0

0.2

0.4 0.6

0.8 1

x 10 -3

-5

0

5

10

x 10-4

-10

-5

0

5

x 10-4

LF

HF

VF

00.2

0.4 0.6 0.8 1 x 10 -3

-5

0

5

10

x 10 -4

-10

LF HF

VF


ISSN: 1790-2769 112 ISBN: 978-960-474-024-6

The value of volume loss was plotted against time as shown in Fig. 4. The general shape of this curve is in agreement with Taylor Tool Life curve. The result clarifies a typical wear growth. The Taylor curve was observed accordingly to the trend of wear rate progression. Due to the higher initial running-in wear rates, it has a higher value initially and will reach a steady state value when the wear rate becomes constant. Three stages were developed in the graph which consists of an initial rapid (running-in period), followed by relatively steady state and the final rapid stage. Wear at the final stage indicates that the wear rate began to acceleratey-axis and the K was plotted in the x-axis.

0 20 40 60 80 100 120 140 160

0

0.5

1

1.5

2

2.5

3

Time (min)

Vol

ume

loss

(mm

3)

Break-in period

Steady-state region

Failure region

FIGURE 4 0.3T0.260= 0.795 curve fitting of bearing wear loss

Morphology of the worn samples after wear tests revealed that significant grooves had occurred. In the present study it has been observed that after 500 m sliding distance deep grooves as well as detachment of wear particles that indicate the occurrence of metal to metal contact during running-in period had occurred (Fig. 5a). It has also been found that an extended in sliding periods exhibited less grooves suggesting that better wear resistance had occurred as shown in Fig. 5(b) while in Fig. 5(c), very small surface damages were detected. This finding leads to the conclusion that, at 500 m the pin surface is covered with more wear particles as a result of a higher wear rate, due to more asperities removal caused by a higher surface roughness. However, when the pin is tested in the steady-state wear regime with a sliding distance of 8000 m, the amount of debris present on the surface of the pin is greatly reduced due to a lower wear rate [11], as shown in Fig. 5.

(a)

(b)

(c)

FIGURE 5 Morphology of worn bearings after lubricated wear at 30 N normal loads for a) 500 m, (b) 1200 m and (c) 2400 m. 5 Conclusion Bearing wear from signal data distribution was analysed using I-kaz method. The signal data varies accordingly to the wear condition. From this preliminary experimental result, wear coefficient, K’ was obtained from a volume loss versus sliding distance. It was found that the K’ ranges between 4.4x10-5 to 8.5x10-5

mm3/Nm, indicating a moderate wear condition. Based on the morphology investigation it can be concluded that


ISSN: 1790-2769 113 ISBN: 978-960-474-024-6

[7] O. Garret, P. Young, K. Kevin, G. Byrne. Towards the improvement of tool condition monitoring systems in the manufacturing environment. Journal of Material Processing Technology. Vol. 119, no. 1-3, 2001, pp. 133-139.

under lubricated test, an increase in the sliding distance may lead to a better wear resistance. I-kaz coefficient, Z∞ which was plotted against sliding distance concludes that K’ and Z∞ were proportional to each other. During the run-in period gave a high value of Z∞ 8.35x10-12 was found and towards the end of experimental work the Z∞ value dropped drastically to 3.05x10-12. It can be justified that the bearing progresses toward catastrophic failure at the end of the experiment. The trend of the Z∞ may also depend on certain mechanical characteristics of the bearing like the bearing running speed and load. By observing the pattern of bearing wear, I-kaz method was possible to be applied by integrating the Taylor Tool Life curve as an alternating technique to monitor bearing wear condition. Therefore additional experiment should be carried out to validate further the correlation between bearing wear progress and the Taylor curve obtained. It was found that the combination of numerical descriptor of Z∞ and graphical representation, display a summary of signal data distribution. Therefore, I-kaz method is a reliable tool in condition monitoring.

[8] J.K. Lancaster. The influence of substrate hardness on the formation and endurance of molybdenum disulphide films. Wear. Vol. 10, 1967, pp. 103-117.

[9] I. Daubechies. Ten lectures on wavelets. 1992. SIAM, Philadelphia.

[10] E. Robinowicz. The least wear. Wear. Vol. 100, 1984, pp. 533 – 541.

[11] L.J. Yang. A test methodology for the determination of wear coefficient. Wear. Vol. 259, 2005, pp.1453-1461.

Acknowledgement The authors wish to acknowledge UKM-GUP-BTT-07-25-160, for the research grant. References: [1] S. Janjarasjitt, H. Ocak and K.A. Loparob. Bearing

condition diagnosis and prognosis using applied nonlinear dynamical analysis of machine vibration signal. Journal of Sound and Vibration. Vol. 317, 2008, pp. 112-126.

[2] D. Mba. The Use of Acoustic Emission for Estimation of Bearing Defect Size. Journal of Failure Analysis and Prevention. Vol. 8, 2008, pp.188–192.

[3] R. Martin, F. Honarvar. Application of statistical moments to bearing failure detection, Applied Acoustics. Vol. 44, 1995, pp. 67–77.

[4] R.B.W. Heng, M.J.M. Nor. Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition, Applied Acoustic. Vol. 53, 1998, pp. 211–226.

[5] M.Z. Nuawi, M.J.M. Nor, N. Jamaludin, S. Abdullah, F. Lamin and C.K.E. Nizwan. Development of Integrated Kurtosis-Based Algorithm for Z-Filter Technique. Journal of applied sciences. Vol. 8, 2008, pp. 1541-1547.

[6] M.Z. Nuawi and M.J.M. Nor. Determination of cutting tool wear using I-kaz method. Proc of Advanced Process and System in Manufacturing. 2005, pp. 71-79.


ISSN: 1790-2769 114 ISBN: 978-960-474-024-6

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