Vibration Analysis

Vibration analysis 

helps you monitor and detect issues using vibration data. Read about vibration analysis methodology, tools and techniques, vibration analysis measurement methods, and more.

While accelerometers are still the most common tool used to collect vibration data, modern technology and improved sensor technology have allowed for non-contact, high-speed laser sensors that can detect issues accelerometers can't. This allows for a more accurate and more localized analysis, and opens up vibration analysis to more methodology. Vibration analysis is generally broken down into four principles, and each principle gives you specific information on the working conditions and features of the vibrating parts.

1. Time domain: When a vibration signal is picked up from a transducer (device that converts a physical quantity into an electrical signal) and displayed on the screen of an oscilloscope, it's called a waveform. This signal is in the time domain. The time domain is amplitude plotted against time. While most machine vibration issues are detected using spectrum analysis, some types are more easily seen in waveform.
2. Frequency domain: When the waveform discussed earlier is subjected to spectrum analysis, the end result is a picture of frequency vs. amplitude, known as a spectrum. The spectrum is in the frequency domain like the vibration is in the time domain. Most in-depth analysis of machinery vibration is done in the frequency domain or using spectrum analysis.
3. Joint domain: Because vibration signals vary with time, calculating more than one spectrum at once can be useful. To do this, a joint time technique called Gabor-Wigner-Wavelet can be utilized. This technique is used to calculate variations of the fast Fourier transform (discussed below), including short-time Fourier transform (STFT).
4. Modal analysis: Modal analysis takes measured frequency response functions of a piece of machinery and puts them into a computer model. The computer model can be displayed with animations of all the different vibration modes. The model can be adjusted by either adding to or taking away things like mass or stiffness to see the effects.

Outside of these four basic principles lie numerous forms of analysis, calculations and algorithms used to determine different aspects of vibration analysis. These include:

• Time waveform: A time waveform is acceleration vs. time displayed as tables and plots. Time waveforms show a short time sample of raw vibration, revealing clues to the condition of machinery not always clear in the frequency spectrum. A method of employing time waveform vibration signals as a vibration analysis tool is by using FFT.

• Fast Fourier Transform (FFT): FFT is defined as an algorithm used to calculate a spectrum from a time waveform. In other words, it's a calculation intended to break down a signal into all its frequencies. If you'll recall time domain and frequency domain discussed above, FFT converts a signal from the time domain into the frequency domain. Fast Fourier transform is most often used for detecting machine faults like misalignment or unbalance.
• Phase measurement: When talking about vibration analysis, phase is a relative time difference between two signals measured in units of angle as opposed to time. It only works if the two signals being compared are of the same frequency. Phase measurement is used in tandem with FFT to decipher machine faults like loose parts, misalignment and unbalance.
• Order analysis: Order analysis is a variation of FFT analysis and is mostly used to quantify vibrations of machines with varying revolutions per minute (RPM). In other words, order analysis is frequency analysis where the spectrum's frequency axis is shown in orders of RPM rather than hertz. The term "orders" refers to a frequency that is a multiple of a reference rotational speed. For example, if a vibration signal is equal to twice the frequency of the motor's rotation, the order is two.
• Power spectral density (PSD): Power spectral density is calculated by multiplying the amplitude from the FFT by its different forms to normalize it with the frequency bin width (bin width refers to the grouped x-axis values). Think of PSD as looking at "random" vibrations or motion at many different frequencies. PSD accurately compares random vibration signals that have different signal lengths.

• Envelope analysis: Envelope analysis is a form of vibration analysis that can detect impacts with very low energy often hidden by other vibration signals. It's a popular diagnostic tool for damaged gear teeth and roller bearings.
• Orbit: The orbit is defined as a plot of a sleeve bearing journal's centerline. It's measured by placing two probes in the bearing housing 90 degrees apart. Data from these probes can be displayed digitally and used to detect shaft vibrations caused by oil whirl - oil whirling around inside, causing the journal to move.
• Resonance analysis: Resonance analysis identifies all the natural vibrations and frequencies in machines. The presence of resonance means high vibration, which could reach damaging levels.

Benefits of Vibration Analysis

• Predictability. Give maintenance staff time to schedule required repairs and acquire needed parts.
• Safety. Take faulty equipment offline before a hazardous condition occurs.
• Revenue. Incur fewer unexpected and serious failures, helping to prevent production stoppages that cut into the bottom line.
• Increased maintenance intervals. Extend life of equipment and schedule maintenance by need.
• Reliability. Incur fewer unexpected or catastrophic failures because problem areas can be anticipated before failure.
• Peace of mind. Build confidence in maintenance schedules, budgeting, and productivity estimates.