The diagnosis of rotating and reciprocating machinery has been an area of active research_x000D_ for several decades, for both commercial and military equipment. Most researchers are_x000D_ knowledgeable concerning instrumentation and signal analysis algorithms, but not as_x000D_ experienced with the 'physiology' of various machinery, the details and dynamical behavior of _x000D_ which can be quite complex. Therefore, the tendency has been to use either simple rule-based_x000D_ look-up tables, or in the other extreme ti apply adaptive learning, neural nets, or other_x000D_ data-driven statistics-based approaches that look for anomalies in a manner that attempts_x000D_ to be machine-agnostic. These approaches can be useful in some applications. However, the_x000D_ authors suggest that a superior approach is the use of physics-based set of algorithms that_x000D_ are based on the mechanical and fluid-dynamic (or electrical for motors/generators) details_x000D_ of the machinery in question. Some examples are provided of such algorithms that have_x000D_ application over broad classes of machinery. It is demonstrated how such as approach can_x000D_ be blended with ISO standards based constraints and guidelines to provide software_x000D_ that can mimic much of what an experienced machinery engineer or technician would_x000D_ conclude from a given data set. Examples of machinery successfully diagnosed by the_x000D_ approach will be given.
During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is utilized in choosing transducer and modal hammer impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is utilized to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. A qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.
This paper presents a case study in diagnosing an excessive pipe vibration due to a beating phenomenon. The outdoor process pipes in a sewage plant were found to vibrate viciously and result in loud hamming noise affecting the surrounding community. The process pipes were connected to two identical blower units, each driven by a motor via belt and pulley system. Besides the loud noise, the excessive pipes vibration also posed a concern to the plant personnel that the possibility of premature machine failures may occur if the problem persists any longer. A comprehensive vibration investigation was conducted to map-out the vibration of the entire machine train that includes pipes, blowers, motors, skid, plinth and floor slab of the blower house. Vibration investigation found that pipes vibration was most severe when the two units of blowers were operating simultaneously. It was found that the root cause of the excessive pipe vibration was caused by beating phenomenon of which two adjacent machines operating under a slightly different speeds, of which in this case, the two blowers were operating at 41.88Hz and 41.72Hz respectively. Beating is a phenomenon of constructive and destructive interference of two identical waveforms with slightly different frequency. The remedy measure undertaken was thus to fine tune the operating speed of the two blowers. It was found that pipes vibration had subsided considerably when the two blowers speeds were adjusted 7.5 Hz apart, or fine-tuned to operate at the speed of 42.5Hz and 50Hz respectively. As a result, the loud humming noise emitted from the pipes was also noticed to have disappear altogether.
