Vibration Analysis
Vibration Analysis
Vibration analysis is the process by which there is evaluation of the condition of an equipment with an aim of ensuring that there is avoidance of its failures.
Causes of vibration
Wear
A vibration can be caused due to the wearing out of components like roller or ball bearings, gears or drive belts. That is, a gear tooth which is heavily chipped or worn produces vibration (Agrawal and Evan-Iwanowski, 2011).
Shaft run-out/ misalignment
When a machine’s shaft is not in line, it can cause vibration. Similarly, when any parts of a machine are misaligned, the resultant can be a vibration.
Imbalance
When an unbalanced weight is rotating around the axis of a machine, it creates a centrifugal force which finally amounts to vibration.
Looseness
A component which is loosely attached to its mounts or has loose bearings results in a vibration.
Why to do vibration analysis
Vibration analysis is carried in order to enable the maintenance personnel to be able to minimize any unplanned downtime through a way of scheduling the required repairs to be undertaken on normal maintenance shutdowns of the machine/equipment (Belyaev and Langley, 2011).
The process of vibration analysis helps in deducing the comprehensive spectrum of information essential in interpreting the vibration signature of a rotating equipment. Through vibration analysis, the user or an expert learns on how to identify loose or bent parts, a defective bearing, and misalignment in an equipment.
It is vital recognizing that a cost of hundreds of thousands of dollars can be incurred per hour due to unscheduled downtime. Therefore, the modern vibration analysis software and equipment facilitate the process of predicting developing problems in order to carry out the repairs in real time before disaster strikes. Even though, these sophisticated equipment offer a number of automated capabilities and features; it’s necessary that one has the basic understanding of vibration analysis in order to effectively make use of them. When the personnel of the plant maintenance has such information, there is a fewer occurrence of emergencies.
Application of vibration analysis
A common application of the vibration analysis is its use in identifying and suppressing the unwanted vibration in order to improve the product quality. This application ensures that one is introduced to the basic aspects of structural vibration. The unwanted vibration might result in fatigue or lower the structure’s performance, making it desirable to reduce the impacts of vibration.
Vibration analysis is also applicable in making a quick calculation of the frequency spectrum particularly from a recorded vibration signal (Vierck, 2009). The invention of personal computers and the advancement of the digital processing of signals has that the equipment is suitable laboratory tools which are portable units for the purpose of field use.
Vibration analysis has offered a revolutionized application in the machinery diagnostics. This has been made possible due to the coupling of the device with computer programs which store data and take provide care for the logistics of collecting vibration data.
Tools and equipment used in vibration analysis
Fluke 805 FC Vibration Meter
This tool offers a repeatable, accurate and reliable way for checking the bearings and the overall vibration of a machine.
Fluke 820_2 LED Stroboscope
The equipment identifies the running speed of a rotating part of a machine.
Fluke 830 Laser Shaft Alignment Tool
The tool is used for a précised shaft alignment.
Fluke 810 Vibration Tester
It is used in identifying and prioritizing the mechanical problems.
Advantages of vibration analysis
A number of vibration analysis equipment has data collection store and programs which bear information in a database (Wolf and Deeks, 2014). The vibration analysis process, therefore, ensures that making the most of such programs entailed working with a service center which ensures comprehensive repair reports, inclusive of the manufacturer and the bearing size. The process has absolutely eradicated chances of guesswork in case a problem arises.
The invention of microprocessors has greatly improved the process of vibration data analysis and acquisition (Myklestad, 2014). The vibration analysis technological advancement has ensured that the measurement tasks which several hours in about two decades ago now can be completed seconds and there is an effective process of decision-making since there is a better presentation of data.
Additionally, the vibration analysis has brought about reliability as fewer catastrophic or unexpected failures can be experienced as the process ensures that the areas with any sort of problem are anticipated early enough before their actual failure.
Vibration analysis has been used in providing early signs to warn of the several potentially severe problems within rotating machinery (Cartmell, 2013). It is, therefore, a predictive maintenance measure in which a firm can save on its budget reliability concepts as it reduces the spare parts inventory, reducing downtime and thus increasing productivity.
Moreover, the predictability aspect of vibration analysis is a significantly essential concept of the system since it gives the maintenance staff enough time to ensure timely scheduling of required repairs and put in place the needed parts in advance.
The vibration analysis has resulted in simplified data analysis and acquisition. The combined power of system software and data collector, the data acquisition process, has been narrowed to a system of simple measurement routes which require limited operator input. The role of the technician is, therefore, to temporarily support a transducer at the appropriate measurement point and then push a button. The process is simplified as the microprocessor automatically evaluates, acquires and assesses the conditions and finally stores the deduced vibration data (Dukkipati, 2014).
Limitations of vibration analysis
Despite providing a number of advantages, the simplified data analysis and acquisition can pose great demerit. In the case of an improperly configured database, the automated capabilities of the entire process of vibration analysis will result in faulty diagnostics which can consequently result in disastrous failure of the equipment.
Moreover, the reduction to a minimum level of the technicians’ involvement poses great impediment as the firms resort to untrained or individuals who are partially trained to perform this repetitive function (Liu, 2013). This lack of expertise causes less awareness and knowledge of the audible and visual clues which should be considered as an integral segment of the monitoring program.
Furthermore, there is a challenge of the system’s steady-state data. A good number of the microprocessor-based equipment are designed for handling of steady-state vibration data (Jennings, 2013). Only a few of these instruments can effectively capture transient data, for example, load changes or rapid speed. This has made their use to be limited in scenarios where these occur.
In addition, the most predictive maintenance programs do rely exclusively on the frequency-domain vibration data. Microprocessor-based analysis collects time-domain data which is automatically converted by use of fast Fourier transform (FFT) to the frequency-domain data (Ganesan and Dhotarad, 2013). Though analysis of the frequency-domain data is relatively much easier to understand than analysis of the time-domain data, it doesn’t have the ability to identify and isolate all the incipient problems that the installed system or the machine is having. Therefore, to derive to an absolute diagnostic picture, the analysis frequency-domain data must be used conjunctively with multichannel, time-domain, and real-time analysis.
Lastly, vibration analysis experiences the sing-channel data problem. A good number of the monitoring systems pegged on microprocessor-based vibration collect single-channel, steady-state data which cannot be supported by all the applications. The single-channel data only apply to the extent of analysis of the simple machinery which operates at considerably constant speed (Girdhar and Scheffer, 2012).
Sample graphs, diagrams, pictures.
3.58 minutes video on Natural Frequencies, Mode Shapes & Vibration.
Bibliography
Agrawal, B. and Evan-Iwanowski, R. (2011). Nonstationary and Nonlinear Vibration Analysis. The Shock and Vibration Digest, 11(8), pp.19-22.
Belyaev, A. and Langley, R. (2011). IUTAM Symposium on the vibration analysis of structures with uncertainties. Dordrecht: Springer.
Cartmell, M. (2013). Modern practice in stress and vibration analysis. Uetikon-Zuerich, Switzerland: Trans Tech Publications.
Dukkipati, R. (2014). Vibration analysis. Harrow, Middlesex: Alpha Science International.
Ganesan, N. and Dhotarad, M. (2013). Vibration analysis of mindlin plates. Journal of Sound and Vibration, 87(4), pp.643-645.
Girdhar, P. and Scheffer, C. (2012). Practical machinery vibration analysis and predictive maintenance. Amsterdam: Elsevier.
Jennings, A. (2013). Eigenvalue Methods for Vibration Analysis. The Shock and Vibration Digest, 12(2), pp.3-16.
Liu, B. (2013). Adaptive harmonic wavelet transform with applications in vibration analysis. Journal of Sound and Vibration, 262(1), pp.45-64.
Myklestad, N. (2014). Vibration analysis. New York: McGraw-Hill.
Vierck, R. (2009). Vibration analysis. New York: Crowell.
Wolf, J. and Deeks, A. (2014). Foundation vibration analysis. Amsterdam: Elsevier.
