Construction of health indicators for condition monitoring of rotating machinery: A review of the research
The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
Prognostics and health management: A review of vibration based bearing and gear health indicators
Prognostics and health management is an emerging discipline to scientifically manage the
health condition of engineering systems and their critical components. It mainly consists of …
health condition of engineering systems and their critical components. It mainly consists of …
Modified varying index coefficient autoregression model for representation of the nonstationary vibration from a planetary gearbox
Planetary gearbox fault detection is important in terms of life-threatening failure prevention
and maintenance optimization. This article focuses on the representation of the planetary …
and maintenance optimization. This article focuses on the representation of the planetary …
Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
Much research has been conducted in prognostics and health management (PHM), an
emerging field in mechanical engineering that is gaining interest from both academia and …
emerging field in mechanical engineering that is gaining interest from both academia and …
Multipoint optimal minimum entropy deconvolution and convolution fix: application to vibration fault detection
GL McDonald, Q Zhao - Mechanical Systems and Signal Processing, 2017 - Elsevier
Abstract Minimum Entropy Deconvolution (MED) has been applied successfully to rotating
machine fault detection from vibration data, however this method has limitations. A …
machine fault detection from vibration data, however this method has limitations. A …
Blind deconvolution based on cyclostationarity maximization and its application to fault identification
Blind deconvolution algorithms prove to be effective tools for fault identification, being able
to extract excitation sources from noisy observations only. In this scenario, the present paper …
to extract excitation sources from noisy observations only. In this scenario, the present paper …
Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection
In this paper a new deconvolution method is presented for the detection of gear and bearing
faults from vibration data. The proposed maximum correlated Kurtosis deconvolution method …
faults from vibration data. The proposed maximum correlated Kurtosis deconvolution method …
Review of automatic fault diagnosis systems using audio and vibration signals
The objective of this paper is to provide a review of recent advances in automatic vibration-
and audio-based fault diagnosis in machinery using condition monitoring strategies. It …
and audio-based fault diagnosis in machinery using condition monitoring strategies. It …
The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis
N Sawalhi, RB Randall, H Endo - Mechanical Systems and Signal …, 2007 - Elsevier
Spectral kurtosis (SK) represents a valuable tool for extracting transients buried in noise,
which makes it very powerful for the diagnostics of rolling element bearings. However, a …
which makes it very powerful for the diagnostics of rolling element bearings. However, a …
Anomaly detection and fault prognosis for bearings
In this paper, a new bearing anomaly detection and fault prognosis method is proposed. The
method detects bearing anomalies and then predicts its remaining useful life (RUL). To …
method detects bearing anomalies and then predicts its remaining useful life (RUL). To …