Advances in condition monitoring of rotating machineries

Due to the growing importance of condition monitoring in industries, lots of condition monitoring techniques abound in today’s engineering literature. Actually, recent trends indicate that more condition monitoring strategies are being developed or proposed; this trend currently shows no signs of slowing down and is likely to continue for a long time. A majority of the condition monitoring methodologies are developed specifically for rotating machinery problems; fortunately, this has led to an improved understanding of the observed machineries and what to look out for while these machineries are under observation. Of particular interest in these machineries are shafts, bearings and gears, which are always vital components, but at the same time, are also the major source of failures. Both gears and bearings have unique vibration signatures that can be used to identify them, and thus, the source of failures in machineries. These vibration signatures are not easily observable, so effective condition-monitoring activities require the application of robust signal processing techniques. Analyses performed using any of the available numerous signal processing techniques can be done in the time domain, frequency domain or time-frequency domain, each of which offering its own unique advantages and properties. More recently, some peculiar methods have surfaced as condition monitoring tools. The peculiarity of these methods arises from the fact that they were not developed originally with the intent of using them for condition monitoring purpose, which by the way, makes the operating procedure of these methods noteworthy. The aim of this thesis is to conduct thorough and objective analyses and evaluations of some of these methods while outlining their strengths and weaknesses, and proposing ways to enhance them. The research activities here focus on rotating machineries since they actually form a bulk of machineries that are used in practice. At the end, it is hoped that results of the analyses in this thesis will guide both old and new users in the usage of these methods, while creating a platform for extensive discussions on these methods as well as pathways for new techniques that may arise from these methods.