Gearbox Damage Diagnosis Using Novel Wavelet Technology

L. Gelman; K. C. Gryllias; B. Shaw; M. Vaidhianathasamy

Gearbox Damage Diagnosis Using Novel Wavelet Technology

L. Gelman, K. C. Gryllias, B. Shaw, M. Vaidhianathasamy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The wavelet diagnostic technology is applied for the detection of natural micro pitting on a back-to-back experimental gearbox test rig and the possibility of early detection/diagnosis of local tooth faults is shown. A number of parameters are considered and selected (features, time resolution etc.). A novel automatic decision making technique based on the likelihood ratio is used for damage diagnosis. Novel results in world-wide terms have been achieved: the technology provides an early effective detection/diagnosis of micro pitting in gears with relative pitting size 0.3 - 0.7%.

Original language	English
Title of host publication	7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010
Subtitle of host publication	CM 2010/MFPT 2010
Publisher	British Institute of Non-Destructive Testing
Pages	1194-1202
Number of pages	9
Volume	1
ISBN (Print)	9781618390134
Publication status	Published - 2010
Externally published	Yes
Event	7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies - Stratford-upon-Avon, United Kingdom Duration: 22 Jun 2010 → 24 Jun 2010 Conference number: 7

Conference

Conference	7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies
Abbreviated title	CM/MFPT 2010
Country/Territory	United Kingdom
City	Stratford-upon-Avon
Period	22/06/10 → 24/06/10

Cite this

@inproceedings{12e09e34e09642b7be07e0b932c8d76f,

title = "Gearbox Damage Diagnosis Using Novel Wavelet Technology",

abstract = "The wavelet diagnostic technology is applied for the detection of natural micro pitting on a back-to-back experimental gearbox test rig and the possibility of early detection/diagnosis of local tooth faults is shown. A number of parameters are considered and selected (features, time resolution etc.). A novel automatic decision making technique based on the likelihood ratio is used for damage diagnosis. Novel results in world-wide terms have been achieved: the technology provides an early effective detection/diagnosis of micro pitting in gears with relative pitting size 0.3 - 0.7\%.",

keywords = "Failure analysis, fault detection, Planetary gearbox",

author = "L. Gelman and Gryllias, \{K. C.\} and B. Shaw and M. Vaidhianathasamy",

year = "2010",

language = "English",

isbn = "9781618390134",

volume = "1",

pages = "1194--1202",

booktitle = "7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010",

publisher = "British Institute of Non-Destructive Testing",

address = "United Kingdom",

note = "7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM/MFPT 2010 ; Conference date: 22-06-2010 Through 24-06-2010",

}

Gelman, L, Gryllias, KC, Shaw, B & Vaidhianathasamy, M 2010, Gearbox Damage Diagnosis Using Novel Wavelet Technology. in 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010: CM 2010/MFPT 2010. vol. 1, British Institute of Non-Destructive Testing, pp. 1194-1202, 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Stratford-upon-Avon, United Kingdom, 22/06/10.

Gearbox Damage Diagnosis Using Novel Wavelet Technology. / Gelman, L.; Gryllias, K. C.; Shaw, B. et al.
7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010: CM 2010/MFPT 2010. Vol. 1 British Institute of Non-Destructive Testing, 2010. p. 1194-1202.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Gearbox Damage Diagnosis Using Novel Wavelet Technology

AU - Gelman, L.

AU - Gryllias, K. C.

AU - Shaw, B.

AU - Vaidhianathasamy, M.

N1 - Conference code: 7

PY - 2010

Y1 - 2010

N2 - The wavelet diagnostic technology is applied for the detection of natural micro pitting on a back-to-back experimental gearbox test rig and the possibility of early detection/diagnosis of local tooth faults is shown. A number of parameters are considered and selected (features, time resolution etc.). A novel automatic decision making technique based on the likelihood ratio is used for damage diagnosis. Novel results in world-wide terms have been achieved: the technology provides an early effective detection/diagnosis of micro pitting in gears with relative pitting size 0.3 - 0.7%.

AB - The wavelet diagnostic technology is applied for the detection of natural micro pitting on a back-to-back experimental gearbox test rig and the possibility of early detection/diagnosis of local tooth faults is shown. A number of parameters are considered and selected (features, time resolution etc.). A novel automatic decision making technique based on the likelihood ratio is used for damage diagnosis. Novel results in world-wide terms have been achieved: the technology provides an early effective detection/diagnosis of micro pitting in gears with relative pitting size 0.3 - 0.7%.

KW - Failure analysis

KW - fault detection

KW - Planetary gearbox

UR - https://www.scopus.com/pages/publications/84905736062

UR - https://www.bindt.org/shopbindt/cd-roms/proceedings-of-cm-mfpt-2010.html#.XkZxIij7S70

UR - http://www.proceedings.com/12147.html

M3 - Conference contribution

AN - SCOPUS:84905736062

SN - 9781618390134

VL - 1

SP - 1194

EP - 1202

BT - 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010

PB - British Institute of Non-Destructive Testing

T2 - 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies

Y2 - 22 June 2010 through 24 June 2010

ER -

Gearbox Damage Diagnosis Using Novel Wavelet Technology

Abstract

Conference

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