Facile wear failure monitoring of commercial bearing alloys using I-kaz method

Basit

Proceedings of the Institution of Mechanical Engineers, Part J:

et al. 2017

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.

Section: Methodsmentioning

confidence: 99%

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

Basit

Proceedings of the Institution of Mechanical Engineers, Part J:

et al. 2017

Engineering Failure Analysis

“…The damaged bearing follows a higher clearance and stiffness curve than the fault-free bearing. The stiffness in the intermediate-and high-speed shaft bearings was changed from 9 10 N/m in the fault-free case to 6 10 N/m in the faulty case. However, the planet bearing was found to be too sensitive to the bearing stiffness.…”

Section: 4-fault-free and Faulty Bearing Modelsmentioning

confidence: 99%

“…In gearboxes and drivetrains, noise and vibration signal processing are used for fault detection [4][5][6][7]. For example, Elforjani and Mba [8] as well as Ghazali et al [9] demonstrated the application of 4 acoustic emission technology to detect damage in a single bearing in a test rig. Randall used acoustic measurements and proposed a signal decomposition method to distinguish the signals from gears and bearings in a gearbox [10].…”

Section: -Introductionmentioning

confidence: 99%

A prognostic method for fault detection in wind turbine drivetrains

Nejad

Odgaard

Gao

et al. 2014

“…This has been established since the 1970s [ 6 ]. Studies indicate the effectiveness of analyzing contact based acoustic emissions in order to calculate the wear occurred in a component for various machine processes like sliding, cutting, milling, and tool manufacturing [ 1 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. The spectrum of the obtained acoustic emissions is further processed to measure count rates, RMS voltage, and also FFT analysis [ 10 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

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

Rahman

Mushtaq

2021

Sensors

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.