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Research Papers: Design of Direct Contact Systems

A Step Toward Fault Type and Severity Characterization in Spur Gears

[+] Author and Article Information
I. Dadon

PHM Laboratory,
Department of Mechanical Engineering,
Ben-Gurion University of the Negev,
P.O.B 653, Beer-Sheva 8410501, Israel
e-mail: dadoni@post.bgu.ac.il

N. Koren

PHM Laboratory,
Department of Mechanical Engineering,
Ben-Gurion University of the Negev,
P.O.B 653, Beer-Sheva 8410501, Israel
e-mail: korenni@post.bgu.ac.il

R. Klein

R.K. Diagnostics,
P.O.B 101, Gilon, D.N. Misgav 20103, Israel
e-mail: Renata.Klein@RKDiagnostics.co.il

J. Bortman

PHM Laboratory,
Department of Mechanical Engineering,
Ben-Gurion University of the Negev,
P.O.B 653, Beer-Sheva 8410501, Israel
e-mail: jacbort@bgu.ac.il

1Corresponding author.

Contributed by the Power Transmission and Gearing Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received December 17, 2018; final manuscript received March 24, 2019; published online April 16, 2019. Assoc. Editor: Hai Xu.

J. Mech. Des 141(8), 083301 (Apr 16, 2019) (11 pages) Paper No: MD-18-1901; doi: 10.1115/1.4043367 History: Received December 17, 2018; Accepted March 26, 2019

Gear transmissions are widely used in industrial applications and are considered to be critical components. To date, the capabilities of gear condition indicators are controversial as some condition indicators can diagnose one type of fault at the early stages, yet cannot diagnose other types of faults. This study focused on fault detection and characterization based on vibrations in a spur gear transmission. Three different common local faults were examined: tooth face fault, broken tooth, and cracks at the tooth root. The faults were thoroughly analyzed to understand the fault manifestation in the vibration signature and to find condition indicators that are robust and sensitive to the existence and severity of the fault. The analysis was based on both experimental data and simulated signals from a well-established dynamic model of the gear system. The fault detection capability of common condition indicators, as well as newly defined condition indicators, was examined and measured using statistical distances. For each fault type, the investigated condition indicators were categorized according to their discrimination power between faulted and healthy states and the ability to rank the fault severity. It was concluded that faults that affect the involute profile throughout the tooth are easily detectable. Faults such as root cracks or chipped tooth, in which mainly the tooth stiffness is affected, are much more challenging to detect. It has been shown that while using a realistic model, the capabilities of different condition indicators can be tested, and the experiments can be replaced by simulations.

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Figures

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Fig. 1

Tooth face fault geometric measurements

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Fig. 2

Examples of different sizes of local tooth face faults: (a) TFF 01 and (b) TFF 02

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Fig. 3

Examples of tooth breaking cases: (a) chipped tooth 01 and (b) broken tooth 06

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Fig. 4

Examples of different crack lengths: (a) crack 01, (b) crack 03, and (c) crack 05

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Fig. 5

Variations of the equivalent mesh stiffness as a function of the pinion angular position. H corresponds to the undamaged gears, and faults 01 to 08 correspond to the tooth breakage fault severity.

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Fig. 6

Tooth root crack geometric measurements: (a) front view and (b) isometric view

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Fig. 7

Variations of the equivalent mesh stiffness as a function of the pinion angular position. H corresponds to the undamaged gears and faults 01 to 04 correspond to the crack severity.

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Fig. 8

Experimental system: (a) a scheme and (b) accelerometer location and orientation

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Fig. 9

Generating signals scheme

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Fig. 10

CI processing flow chart

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Fig. 11

Experiments of tooth face fault: (a) D2 (CF (ENV (DIF))), (b) D2 (RMS (ENV (DIF))) versus D2 (Kurt (ENV (DIF))), and (c) D2 (Skew (ENV (DIF))), and (d) D2 (EOP (PA (DIF)))

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Fig. 12

Distance feature D2 (FMΣh) of tooth face fault: (a) experiments and (b) simulations

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Fig. 13

Experiments of tooth breakage fault: (a) D2 (CF (ENV (DIF))), (b) D2 (FMΣh), (c) D2 (Skew (ENV (DIF))), and (d) D2 (EOP (PA (DIF)))

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Fig. 14

Distance features D2 (RMS (DIF)) versus D2 (Kurt (DIF)) of tooth breakage fault: (a) experiments and (b) simulations

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Fig. 15

Experiments of tooth root crack fault: (a) D2 (CF (ENV (DIF))), (b) D2 (FMΣh), (c) D2 (Skew (ENV (DIF))), and (d) D2 (EOP (PA (DIF)))

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Fig. 16

Distance features D2 (RMS (ENV (DIF))) versus D2 (Kurt (ENV (DIF))) of tooth root crack fault: (a) experiments and (b) simulations

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