Sliding wear evaluation of aluminum alloy (7075-T6) on hardened steel (AISI4340) via non-contact technique by I-kaz™ multi-level analysis

Karim, Z.; Nuawi, Mohd. Zaki; Ghani, Jaharah A.; Ghazali, Mariyam Jameelah; Abdullah, Shahrum; Mansor, N.I.I.

doi:10.1016/j.wear.2014.11.012

Cited by 9 publications

(9 citation statements)

References 17 publications

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“…Researchers have applied acoustic emission techniques to detect wear [91][92][93][94][95][96]. Bhuiyan et al [97] used an acoustic emission technique to investigate the frequency of tool wear, and found that the frequency of tool wear is distributed between 67 kHz and 471 kHz.…”

Section: Introductionmentioning

confidence: 99%

Feasibility Study of Real-Time Monitoring of Pin Connection Wear Using Acoustic Emission

et al. 2018

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Pin connections are one of the most important connecting forms and they have been widely used in engineering fields. In its service, pin connections are subject to wear, and it will be beneficial if the health condition of pin connections can be monitored in real time. In this paper, an acoustic emission (AE)-based method was developed to monitor wear degree of low rotational speed pin connections in real time in a nondestructive way. Most pin connections are operated at low rotational speed. To facilitate the research, an experimental apparatus to accelerate the wear test of low rotational speed pin connections was designed and fabricated. The piezoceramic AE sensor was mounted on the test apparatus in a nondestructive way, and it was capable of real-time monitoring. Accelerated wear tests of low rotational speed pin connections were conducted. To verify the results of the AE technique, a VHX-600E digital (from Keyence, Osaka, Japan) microscope was applied to observe the micrographs of the tested pins. The experimental results show that AE activity existed throughout the entire wear process, and it was the most prominent in the serious wear phase. The wear degree of the pin connections can be reflected qualitatively by the signal strength and the accumulative signal strength of the AE signals. In addition, two different wear forms can be distinguished by comparing the signal strength values of all specimens. Micrographs of all specimens confirm these results, and determine that the two wear forms include adhesive wear and abrasive wear. Furthermore, AE results demonstrated that adhesive wear is the main mode of wear for the low rotational speed pin connections, and the signal strength of the adhesive wear is around 190 times larger than that of abrasive wear. This feasibility study demonstrated that the developed acoustic emission technique can be utilized in the wear monitoring of pin connections in real time in a nondestructive way.

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Section: Introductionmentioning

confidence: 99%

Feasibility Study of Real-Time Monitoring of Pin Connection Wear Using Acoustic Emission

et al. 2018

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“…The microphone can measure frequencies of up to 8 kHz similar in range as used in some recent research. 27,28 It is connected to a computer for recording noise for further analysis. The sampling frequency during recording was set at 44.1 kHz with 16-bit sampling.…”

Section: Methodsmentioning

confidence: 99%

“…Noise signals have also been studied under the effect of lubrication [22][23][24]. Recently, researchers have shown the possibility of the trend modeling between noise signals and the wear in terms of accumulated signal energy and changes in spectrum amplitude [10,[24][25][26][27]. However, analysis of airborne noise signals for the wear evaluation of the mechanical components with multiple contact points under load and a lubricated test scheme is still not available and requires an in-depth study.…”

Section: Introductionmentioning

confidence: 99%

Experimental assessment of multiple contact wear using airborne noise under dry and lubricated conditions

Khan

Basit

Khan

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part J:

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Generation of wear and airborne noise is inevitable in mechanical contacts of machine components. This paper addresses the effectiveness of airborne noise data in estimating the wear on a disc under multi-contact conditions. A pin on disc rig was employed to study the role of noise parameters on the evolution of the wear area. When a pin slides on the disc, the airborne noise is generated and subsequently a sound signal is obtained. These signals, for various sets of experiments, were recorded using a digital microphone. A Matlab code was developed and employed to estimate noise parameters from the recorded sound. Noise parameters including values of voltage RMS, noise counts and amplitudes of dominant frequencies were used to analyze the variation in the disc wear at different time intervals. These parameters were found to be effective in the determination of wear damage evaluation under different loads without lubrication.

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“…Contact based signals were also studied under the effect of lubrication in the past [ 23 , 24 , 25 ]. Recently, researchers showed the possibility of the trend modeling between acoustic emissions and the wear in terms of accumulated signal energy and changes in spectrum amplitude [ 9 , 25 , 26 , 27 , 28 , 29 ]. However, most of these efforts used a single pin/point contact sensor and analyzed the spectrum of noise with different speed, sliding distance, and temperature values.…”

Section: Introductionmentioning

confidence: 99%

Predictive Modeling of Surface Wear in Mechanical Contacts under Lubricated and Non-Lubricated Conditions

Rahman

Khan

Mushtaq

2021

Sensors

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The surface wear in mechanical contacts under running conditions is always a challenge to quantify. However, the inevitable relationship between the airborne noise and the surface wear can be used to predict the latter with good accuracy. In this paper, a predictive model has been derived to quantify surface wear by using airborne noise signals collected at a microphone. The noise was generated from a pin on disc setup on different dry and lubricated conditions. The collected signals were analyzed, and spectral features estimated from the measurements and regression models implemented in order to achieve an average wear prediction accuracy of within 1mm3.

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Sliding wear evaluation of aluminum alloy (7075-T6) on hardened steel (AISI4340) via non-contact technique by I-kaz™ multi-level analysis

Cited by 9 publications

References 17 publications

Feasibility Study of Real-Time Monitoring of Pin Connection Wear Using Acoustic Emission

Feasibility Study of Real-Time Monitoring of Pin Connection Wear Using Acoustic Emission

Experimental assessment of multiple contact wear using airborne noise under dry and lubricated conditions

Predictive Modeling of Surface Wear in Mechanical Contacts under Lubricated and Non-Lubricated Conditions

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