Non-invasive methodology for diagnostics of bearing impacts

John N. Chi

doi:10.1117/12.715856

18 April 2007 Non-invasive methodology for diagnostics of bearing impacts

John N. Chi

Proceedings Volume 6523, Modeling, Signal Processing, and Control for Smart Structures 2007; 652310 (2007) https://doi.org/10.1117/12.715856
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2007, San Diego, California, United States

Abstract

Various events in reciprocating machinery, such as connecting rod or piston movement, and diesel combustion produce a series of highly transient forces within the machine. These events generate force transients of short duration and broad frequency content. Even though these events may be part of a machine cycle and therefore periodic, it is often more appropriate to treat them on an individual basis because more diagnostics information is available from a single waveform during a cycle than from averages over several cycles. However, it is very rare for one to have direct access to source waveforms because of the expense and reliability problems associated with the required instrumentation, and non-invasive techniques will have to be used. This paper explores the use of cepstral smoothing and minimum phase extraction technique for non-invasive diagnostics of bearing impacts in reciprocating machinery. The methodology is based on extracting diagnostic signals from vibration measurements taken at a "convenient" location such as the crankshaft casing or bearing end-cap, and consists of source identification, diagnostic signature recovery, and diagnostic system decision-making. A dynamic simulation with lumped mass model is developed to analyze bearing impacts for the big end bearings, experimental measurements from accelerometers, transfer functions of vibration, and the structural response are presented.

Citation Download Citation

John N. Chi "Non-invasive methodology for diagnostics of bearing impacts", Proc. SPIE 6523, Modeling, Signal Processing, and Control for Smart Structures 2007, 652310 (18 April 2007); https://doi.org/10.1117/12.715856

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KEYWORDS

Diagnostics

Fourier transforms

Vibrometry

Signal processing

Smoothing

Computer programming

Electronic filtering

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