In this paper, we demonstrate the effects of rotating machinery shaft misalignment on its dynamic behavior which is characterized in the form of an Operational Deflection Shape (ODS). In this approach, an ODS derived from multiple accelerometer signals acquired at various points on the machine is used to diagnose shaft misalignment.
Tests are performed on a machinery fault simulator under various operating conditions. Operating data is simultaneously acquired using a multi-channel data acquisition system. Since misalignment produces dominant motion at the rotor running speed and its harmonics, this data is used to construct an ODS.
The emphasis is on correlating the ODS of the machine when properly aligned with its ODS following induced shaft misalignment. The results of this work will provide a new perspective of machinery fault detection. The aim is to develop a more reliable tool for determining shaft misalignment and other machine faults from operating data.[/vc_column_text][/vc_column][/vc_row][vc_row][vc_column][vc_column_text]
A poorly aligned machine can account for up to 30 percent of a machine’s downtime. Not only is downtime expensive in terms of lost production, but it also increases costs in the form of more replacement parts, inventory, and energy consumption. Considering the importance of the shaft alignment,
it is interesting to note that a widespread understanding and use of tools for detecting and diagnosing misalignment is still elusive. A survey of the literature reveals that:
1. Misalignment produces significant vibration levels.
2. A machine can have parallel misalignment without exhibiting significant 2X vibration levels.
3. Misalignment is strongly influenced by machine speed and coupling stiffness.
4. Softer couplings are more forgiving, and tend to produce less vibration.
5. Level profiling of a single-point vibration spectrum for a given operating condition does not provide a reliable indication of machinery misalignment.
6. Observation of spectra in several points & directions, at varying speeds, may be needed to effectively diagnose misalignment.
Traditionally, vibration signatures (level profiling of singlepoint vibration spectra), and orbit plots, have been used as the preferred tools for detecting and diagnosing machinery misalignment. Although these tools may be effective when used by an expert, ODS analysis offers a simpler, more straightforward approach to detecting misalignment. Misalignment is more easily characterized by a visual as well as a numerical comparison of a machine’s ODS with its baseline ODS, taken when the machine is properly aligned.
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Figure 1: Accelerometers on Motor & Bearings
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Figure 2: Baseline ODS’s – 2000 & 4000 RPM