Other Monitoring Techniques - Find Out More - Brüel & Kjær Vibro

Other Monitoring Techniques

Modal Analysis

This determines the dynamic response of a machine when physically excited by one or more external forcing functions. This analysis is used primarily to determine natural modes, resonances and damping characteristics of the machine. Resonances can lead to premature failure of the machine components if not reduced or avoided, thus modal analysis is often done to reactively determine the root cause of a machine failure.

Event analysis and post-processing analysis

A time signal is measured and stored at an event trigger or fixed time intervals for later evaluation (post-processing analysis of the time signal) by a specialist. When a time signal is stored at a user-defined time interval before and after a fault has been detected, this is called event analysis. The raw signal can then be post-processed to find out what type of fault has been detected and its severity. A time signal can also be stored at fixed time intervals for machine health assessment. Post-processing analysis is generally done if the automatic condition monitoring measurements (process and frequency conditioned vibration measurements) that detected the fault do not contain enough diagnostic information for planning maintenance action ahead of time. The stored time signal can be opened at any time for time domain or vibration frequency analysis. Frequency analysis includes frequency spectrum, cepstrum, envelope analysis, vector and bandpass.

Fault Detection

In vibration measurements there are many techniques that may be used, but not all techniques are equally well suited for all purposes.
The main challenge for maintenance is to keep track of the current status of the machinery: Are they in good shape – or are they getting worn out, and if so:

  • What is the lead-time to failure,
  • what is the developing fault?

The main objective is: To detect if faults are present.

Therefore the scope is to utilize techniques that easily reveal if any of the possible faults on a machine is present – and developing.

  • The CPB spectra with its wide frequency range and adequate resolution in any frequency range has proven to be the best tool for fault detection.

Selecting the proper technique for fault detection on rotating machinery makes it possible to detect them before the machine breaks down, thereby reducing financial losses, such as damaged equipment and production downtime.

General fault symptoms

Machine faults can be identified by a number of symptoms such as an increase or decrease in bearing temperature or mechanical and acoustic vibration, loss of performance, increase in emissions, etc. In the case of many types of faults, it is often possible to identify an increase in mechanical vibration before other symptoms appear.

Each rotating component in a machine has an effect on the overall vibration picture. These effects can be individually identified by a dissection of the total vibration into its constituent components, to create a clearer view and allow the individual causes to be seen and identified.

The most commonly used method used for this extraction is a frequency spectrum analysis – better known as an FFT. However some faults are easier to identify using a phase analysis – e.g. misalignment – due to the fact that an FFT does not show the phase information. Other types of faults, e.g. certain gear faults, require the original time-signature or a Cepstrum analysis to be identified.

However the task of accurately diagnosing faults is nevertheless a complex one and requires intensive training, experience, powerful vibration analysers and detailed technical information about the machine.


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