Practical Applications

FREE FOR MEMBERS

Individual membership and corporate sponsorship in the Vibration Institute includes

Member Log In

SPECIAL OFFER!

Become a Vibration Institute Member today for only $95 and get access to the entire document library at no charge.

Become A Member

BUY IT FOR $99

Only interested in this article? You can make a one time purchase to download this content.

Purchase Now

The Practical Applications of Signal Processing

by Nelson L. Baxter, P.E.

Abstract

Digital signal processing CAN cause false readings if correct precautions are not taken. Many examples of WHERE and HOW these errors occur are given and precautions are listed that can help you avoid these errors. Examples given demonstrate that these errors may occur much more frequently than you would imagine. Incorrect spectrum used for analysis give rise to BAD decisions about machine condition. BE CAREFUL.

PREVIEW

“Digital signal processing has brought forth many positive changes to the field of vibration analysis. Dedicated DSP chips have made it possible to perform spectrum analysis, with small portable devices. For the most part, the conversion of analog signals to a series of numbers, that can be stored and processed into spectra has been a good thing. However, as with most things there are other aspects of this conversion that produce unexpected side effects.

What happens if instead of sine waves, the signals are impacts? What happens if during the time in which the block of data was obtained, the amplitude varies? What happens if during the acquisition period the frequency changes? What happens if the signal does not start and end with zero for the block of data that will be analyzed? As it turns out, these are all valid questions, because they can greatly influence the spectral outputs.

ANTI-ALIASING FILTERS

Whenever data is sampled by the A/D converter there must not be any signals present which are greater than half the sampling rate. Another way of looking at it is that two samples must be taken for each cycle of the highest frequency sine wave that is being sampled.”

THE FFT PROCESS: Without going into a great deal of detail, the FFT process consists of:

Sampling analog signals with an ND converter to produce a series of discrete numbers that represent the time signal from the transducer and then storing that block of sampled data in a buffer.
The next step is to multiply that block of numbers by a series of numbers that represent sines and cosines at each analysis bin’s frequency. If the series of numbers that represent the analog signal have frequency content that matches the frequencies of the multiplying sines and cosines, then for each frequency where there is a match, there is a value generated which represents that frequency’s amplitude. That output is the value that is seen for a particular frequency in the vibration spectrum. The key point here is that the FFT is a batch process. It works great if the signals being analyzed are sinusoidal, of constant amplitude, are of a constant frequency and if the signals start and end with zero during the period of the block of data that is being processed. Unfortunately, in the real world, such signals are rare.

Vibration Analysis Certifications

The Vibration Institute Training Courses provide unique opportunities to study vibration principles in a way that goes beyond the textbook to provide real-world applications.

Get Expertise

Employers and clients seek the most qualified and knowledgeable professionals. Start your certification today.

Become A Member

Join Now