Bearings: Early detection of failure
24 April 2017
Bearing frequencies are often hidden within a range of machine signals and harmonics, making it difficult to detect bearing faults at an early stage. Chris Hansford, managing director at Hansford Sensors, explains how a sophisticated signal processing technique can overcome this
Detecting wear, imbalance and misalignment of rotating parts within machinery is critical to its health and performance. This can be achieved by implementing a variety of proven techniques. Vibration analysis, for example, uses accelerometers to detect potential problems with industrial equipment caused by incorrectly aligned, loose or unbalanced rotating parts.
These techniques tend to be most effective during the later stages of the wear cycle, when damage is already occurring. In the early stages of wear, however, when vibration signals are of low intensity, it can be difficult to separate the wear signature from underlying and background machine frequencies.
Instead of waiting for wear rates to progress to a later stage – when the performance of machinery is likely to be declining – maintenance and production engineers can take advantage of a signal processing technique called acceleration enveloping.
This enables engineers to overcome the limitations of conventional velocity spectrum measurements and detect the failure of, for example, rolling element bearings at the earliest possible stage. The rate of wear can then be monitored and maintenance work planned accordingly.
In practice, what tends to occur is that a defect in a rolling element causes repeated impact events that generate resonant frequencies in the surrounding machine surfaces, causing it to ring. Although the amplitude of the ringing signal decays between impacts, and becomes part of the overall vibration signal of the machine, it will nonetheless affect the natural resonance response of the machine at the impact frequencies.
Using a high performance accelerometer, acceleration enveloping progressively filters out unwanted parts of the vibration spectrum, until the signal of the bearing defect can be isolated from the noise around it. The signal is then clearly identifiable.
This information can then be easily collected from the accelerometer using a data collector, ready for review and interpretation by a specialist. They will be able to make an informed decision on whether or not maintenance work is required immediately or can be planned as part of routine schedules.
Achieving successful results
While acceleration enveloping in many ways is the ideal option for detecting bearing failure, there are potential limitations that must be taken into account before it is implemented. Plant engineers should consider the suitability of each machine because acceleration enveloping isn’t fit for use with all machines. The technique detects faults involving repetitive, metal-to-metal interactions, which means anything that masks this may reduce its effectiveness.
However, where an application is deemed to be suitable, there are several factors that will help to ensure better results. Firstly, accelerometers to measure low level signals should be selected carefully – in the proper frequency range – to suit the needs of the particular machine or application.
Once specified and ready for use, accelerometers should be correctly mounted in close proximity to the component being monitored on a flat, clean surface to guarantee consistent results. Poor mounting reduces the reliability of results and can make collected data redundant.
Once accelerometers have been installed and calibrated, data readings should be taken at regular intervals over a period of time to allow accurate trend analyses to be produced. This allows a steadily deteriorating condition to be identified and corrective action to be taken.
The potential benefits of acceleration enveloping are clear, but it would be unwise to rely on the technique alone. Implementing it as part of a wider monitoring and analysis regime can be far more effective, helping plant engineers to safeguard the health, performance and productivity of all the assets under their care.