Apparatus
Objectives
Misalignment is a common cause of machinery malfunction. A poorly aligned machine can cost a factory 20% to 30% in machine down time, replacement parts, inventory, and energy consumption. A large payback is often seen by regularly aligning machinery. Operating life is extended and process conditions are optimized.
Vibration signatures are widely promoted for studying machine malfunctions. However, the literature does not present a clear picture of signature characteristics uniquely attributable to misalignment. Different authors report different signatures. There are no reports of systematic, controlled experiments with varying parameters.
This is a report of a systematic series of experiments designed to elucidate the consistent features, if any, of vibration signatures for misaligned machinery. Three machine-operating parameters, coupling types, amount of misalignment and the motor speed, were systematically varied while all other parameters were held constant. The machine was fault-free with the exception of deliberate misalignment, which was varied systematically. Baseline vibration data was recorded for each of the test conditions.
Observations
Results
The purpose of this study is to examine the spectra due to misalignment between the motor and the rotor shafts. Spectral comparisons were made across coupling measurement points on left bearing housing and the motor. The data were compared in both vertical and axial directions. The results at 960 and 2,100 RPM did not show a significant vibration. Thus, detailed data analysis and study was limited to the higher speeds of 1580.
A correlation between misalignment and vibration signature could not be discerned. The data for all cases contained several harmonics. Both axial and lateral vibration was present in all cases. The dominant harmonic varied from condition to condition. As a general rule, as expected, increased misalignment yielded increased vibration peaks. However, an exception to this rule was observed.
Speed seems to have the most dominant effect on vibration spectra and severity. Often 1X vibration had higher peaks, but in many other cases 2X and 4X seemed to have the largest amplitude. The motor accelerometer revealed more higher frequency vibration than the bearing housing.
Coupling stiffness also appears to have a dramatic effect on misalignment vibration spectra. For a given speed and misalignment level, the steel coupling produced the highest vibration followed by the helical beam and then the rubber coupling. Thus, it can be deduced that at a given condition a stiffer coupling produces more vibration than a softer coupling. Also, the correlation does not seem to be linear and simple.
The effect of the amount of misalignment was not as significant except for the steel coupling.
Conclusions
• Misalignment induced vibration is very complex.
• The data show that a machine can have parallel misalignment without exhibiting 2X vibration.
• Softer coupling seems to be more forgiving and tend to produce less vibration than a stiffer coupling.
• Misalignment vibration is a strong function of machine speed and coupling stiffness.
• A single point vibration spectrum for a given operating condition does not provide a good, reliable indication of machinery misalignment
Discussion
The results clearly indicate a significant variation in vibration spectra as a function of operating conditions. Both amplitude of the dominating peak and its location along the frequency axis changes in a complex manner. The data indicate that it is not possible to conclude that the cause of real world machinery malfunction is shaft misalignment just by looking at a single vibration spectrum at an operating condition. A careful examination is essential to differentiate misalignment from other sources of vibration. Some experimentation and cross correlation analysis along with a rotor dynamics model may be necessary to fully diagnose a problem.
Since misalignment vibration seems to be a strong function of coupling type (stiffness) and rotational speed, a detailed rotor dynamics model is needed to develop a predictive model for misalignment vibration spectra. The misalignment phenomenon is non-linear and much more complex.
The results of this study confer with common sense that when two misaligned shafts are joined together by a coupling, the machine structure is subjected to deformation (strain). The deformation will be different at each angle of rotation depending upon the amount and type of misalignment. The corresponding stress will depend upon the stiffness of the machine structure. The spatial Fourier transform of the angular deformation (or stress) curve will contain several terms. Now when the machine starts turning, the angularly varying stress will produce vibration at each of the Fourier components, assuming a linear relationship. The problem is complicated further due to the inherent non-linearities of a machine.
The frequencies of peak vibration amplitude, MFS locations and directions were inconsistent even with speed and coupling held constant. Increased speed also caused increased peak vibration with frequency shifts that did not correlate with the speed.
As another general rule, peak vibrations in the misaligned machine were in the axial direction. An exception to this rule was also seen.
For predictive maintenance applications where the goal is machinery health monitoring, it is sufficient to realize that the problem is complex. One can routinely trend the vibration spectra until it becomes severe. But for root cause analysis, one must exercise caution and perform a detailed analysis. Obviously, the rules provided in training courses and wall charts are doubtful at best.
The observed changes that occurred with shifts of speed and misalignment do not show a typical signature for misalignment vibration spectra.
