Manufacturing Trend 2008/07-08, Technical Diagnostics Section

"Instead of firefighting and major repairs"

Condition-based maintenance with vibration diagnostics (III.)

The introduction of condition-based maintenance fully serves the need for reliable yet cost-effective operation of machines. In our technical diagnostics series, we continue with an overview of condition-based machine maintenance technologies, as well as machine condition assessment methods based on vibration measurement and vibration analysis. The most suitable method for assessing the mechanical condition of machines during operation is vibration diagnostics. Vibration-based machine diagnostics assist in organizing condition-based and reliability-based machine maintenance. The main idea is to estimate the deterioration of the examined machines, the expected lifespan of the machines (or their elements), and the timing of necessary maintenance based on trends established from measurements performed at multiple suitable intervals. The goal is to ensure production with high reliability, without unexpected downtime, ensuring continuous quality, and with minimal maintenance costs (avoiding unnecessary repairs and preventing larger damages from unnoticed minor faults).

Stethoscopes

One of the cheapest and simplest tools for vibration measurement and analysis is the so-called electronic stethoscope. Its use is based on the fact that

many machine malfunctions can be recognized based on the sound of the operating machine, but determining the cause of the fault (the noise source) can be challenging in a noisy environment. The stethoscope's body sound sensor directly captures the "operational" or "malfunction" sounds generated by moving machine parts, and the instrument amplifies and transmits them to the headphones. If a tape recorder can be connected to the stethoscope, recorded noises can later be compared with sound samples, such as the characteristic sound of a bearing fault. Headphones are available for many vibration sensors processing piezoelectric signals, which can be used as stethoscopes with adjustable filters and amplifiers.

Broadband vibration or vibration level measurement

When a simple and easily interpretable measurement procedure providing a machine condition characteristic for rotating equipment is required, then broadband vibration or vibration level measurement is the appropriate method. Handheld instruments for this purpose measure the effective value of vibration velocity (RMS, the square root of the sum of the squares of the vibration components).

The typical frequency range of the measurement is from 10 to 1000 Hz (according to ISO 2372) or from 10 to 3200 Hz (according to the new ISO 10816-3). These ranges cover the most common frequencies characteristic of mechanical problems in rotating machinery. Imbalances, mechanical looseness, resonance, as well as misalignments of shafts and couplings are excellently noticeable. However, it does not provide information on which issue dominates. The use of handheld broadband vibration meters is recommended for measurements on the bearings (or their housings) of rotating machinery, following various vibration evaluation standards. Users without experience are advised to base their evaluation of measurement results on the ISO 10816-3 standard (which replaced the old ISO 2372 and ISO 3945). There are technologies that require stricter requirements than the standard, as well as cases allowing higher vibration levels than the standard permits. Standards generally focus on measuring vibration velocity in mm/s effective value (RMS). The better understanding of the measurement result is aided by interpreting the read value as the average speed of the back-and-forth movement. The effective vibration velocity value best reflects the extent of unwanted phenomena and adverse energy (forces). These always cause wear and material fatigue in the machine structure.

Machine condition monitoring with trend analysis

The rate of deterioration of machine condition is the most valuable information for organizing condition-based machine maintenance, as it allows estimating when and what intervention is needed to ensure the machine operates without unexpected shutdowns (and unnecessary repairs) while avoiding greater damages due to existing minor faults. To achieve this, the trend of machine vibrations must be created, with the rate of increase providing information on expected durations. The method of trend analysis is very simple: at regular intervals, the vibrations of the machines must be re-measured (at the same locations, in the same direction, and preferably with the same measuring instrument), and the data for each measuring point must be evaluated graphically over time. Considering the interpretable threshold values for each machine, it can be estimated when the vibrations of our machine will reach the limit(s) under unchanged loads and other conditions, indicating the latest time for intervention. For many small and medium-sized companies with a large number of machines, it is no longer advisable to simply "walk through the equipment with paper and pencil," recording the vibration levels of each machine individually, then creating separate graphs or transferring the data to a computer one by one. It is much more worthwhile to invest in a measuring instrument capable of measuring the effective value of vibration velocity and storing the data of multiple machines, as well as transmitting them to a computer. The necessary instruments can be obtained at a relatively favorable price, and their application brings significant benefits, as maintenance planning becomes timely. Knowing when adjustments, balancing, or bearing replacements need to be performed helps avoid unnecessary repairs and unexpected machine downtime.

Precise fault detection with spectrum analysis

The spectrum and frequency analysis of vibrations is not just a mere "trend", but currently the most effective machine condition monitoring tool, provided that the information it contains is "read" with expertise. While the machine condition monitoring and surveillance technologies presented so far do not require specially trained personnel, spectrum analysis can only be effectively applied with appropriate training and experience. The basis of spectrum analysis is the following train of thought: Every machine or machine component (shaft, casing, support element, bearing, disc, etc.) as a "rigid" body has the fundamental mechanical (physical) property that it is most capable of performing vibrations in certain directions at each "own" frequency (thus resonating at this frequency due to external excitation, in our case, for example, due to alternating forces originating from the machine's rotation). Through spectrum analysis of the recorded vibration signal, it becomes "visible" what frequency vibrations are present. However, vibration frequencies can be assigned to certain machine components and typical machine faults, taking into account the current machine speed. Through spectrum analysis of vibrations, the faults of individual machine elements can be precisely detected, and it can be determined whether there is a misalignment or imbalance error. For example, in the case of a bearing fault, this method is capable of separately identifying damage to the inner, outer ring, or the cage. By measuring the electrical parameters of electric motors, electrical faults (including breakage of rotor bars of asynchronous motors) can be detected. Through the analysis of machine vibrations, it is possible to know exactly what needs to be done even before repairs. Significant savings can be achieved in terms of components and working hours, and moreover, during repairs, it is not possible to overlook the correction of less noticeable but also present faults. Furthermore, the success of repairs can be quickly and accurately verified by comparing the spectra of measurements taken before repairs and during recommissioning. The reliability of machines repaired and checked in this way greatly increases while maintenance costs decrease. Rahne Eric (PIM Ltd.) pim-kft.hu, gepszakerto.hu

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