Now that you have the sensor, something needs to capture and record the sensor’s output! Data acquisition systems do just as the name implies: collect/acquire data. The global leader in DAQ systems is National Instruments; but there are many other options out there too. National Instruments offers unparalleled customization options with both their modular hardware and their software program, LabVIEW. Measurement Computing offers some more cost effective alternatives to National Instruments; but they’re less well-known and trusted. For the more advanced user there are systems like m+p International’s VibRunner that can capture 100s of channels for modal analysis applications on larger structures. Something like this will cost tens of thousands of dollars, whereas low-channel systems will cost hundreds or thousands of dollars.
The sensor selection will often dictate the type of DAQ system that will work based upon the sensor’s output. Does the sensor have a digital output? Is it 0 to 30 volts, is ±5 volt? Low sensitivity sensors may require amplification of their output. It will simplify your shock and vibration measurement system setup significantly too if the DAQ system can provide the excitation voltage to your sensor to power it so that clunky power supplies can be avoided.
It’s good practice to sample at a rate 10 times greater than the upper interested frequency range to accurately capture the vibration profile. For most shock and vibration measurement applications a DAQ system will need a sample rate of at least a few thousand hertz; but it all depends on what frequency range that your or customer is concerned about. Take for an example an excerpt of vibration data recorded on a test aircraft shown in Figure 5. The data sampled at 2,500 Hz is made up of many different frequencies ranging from 50 to 600 Hz. Now if this same dataset is sampled only at 500 Hz (shown in the dashed red line), the vibration environment looks much different and would be inaccurately represented.
General guidelines on sample rate are over 10,000 Hz for shock testing, over 5,000 for general vibration, and around 1,000 Hz for slower vibration or movement.
Resolution is generally specified as bits which can then be used to calculate the resolution in acceleration units. For example let’s say that an accelerometer system has 16-bit resolution; this means that it has 216 (65,536) acceleration levels or bins it can measure. Figure 6 illustrates the importance of resolution on a simple 60 Hz sine wave with two lines of different resolutions. 5-bit resolution provides 25 discrete acceleration levels that can be detected while 5-bit resolution only provides 23 or 8 discrete levels.
When looking for a DAQ system they will typically have a resolution on the order of 16 or 24 bits. The lower quality shock and vibration data loggers however may only have a resolution of 12 bits or less which may not be adequate for your application.
Filtering can be used to remove unwanted frequency content and should be an important part of your evaluation of different DAQ systems. High pass filters remove lower frequency vibration and is inherent to all piezoelectric accelerometers (resistor and capacitor in series) which gives these accelerometers the AC response. Low pass filters are more important however to prevent aliasing which can’t be filtered out in software. Aliasing causes a signal to become indistinguishable or to look like a completely different signal as shown in Figure 7. It’s important to realize that an analog lowpass filter is needed to prevent aliasing. Once a signal is aliased, it can’t be filtered out digitally in software.
Now the question remains as to what type of filter should you use? An ideal filter would uniformly pass all frequencies below a specified limit and eliminate all above that limit. This ideal filter would have a perfectly linear phase response to the same upper frequency limit. But ideal filters don’t exist; there is some compromise that needs to be made on a filter’s amplitude and phase response. There are four main different types of filters:
A Butterworth filter is known for its maximally flat amplitude response and a reasonably linear phase response. The Butterworth filter is the most popular for vibration testing.
The Bessel filter has nearly perfect phase linearity so it is best suited for transient events like shock testing. It has a fairly good amplitude response but its amplitude roll-off is slower than the Butterworth or Chebyshev filter.
The Chebyshev has a faster roll-off in the amplitude response which is achieved by introducing a ripple before the roll-off. They have a relatively nonlinear phase response.
The Elliptical filter has the steepest roll-off in the amplitude response but it has a ripple in both the pass band and stop band. In addition, its phase response is highly nonlinear. This is only used for applications where phase shift or ringing is not of a concern; it should generally be avoided to the common test engineer because of its tendency to distort complex time signals.
In Figure 8 the performance of these filters are compared for a 1,000 Hz cut off frequency and 5th order filters. The plots were generated in MATLAB using the Signal Processing Toolbox and the analog filter functions. Figure 9 takes a closer look at the filter performance in the passband (0 to 1,000 Hz). The Chebyshev and Elliptical filters offer that sharper amplitude roll off but at the expense of large ripples in the passband and nonlinearity. Butterworth filters offer the best of both worlds with a relatively sharp amplitude roll off. Bessel has the best phase response and a reasonably good amplitude response but note how early it begins filtering; and in the stopband it still allows over 10% of the single until roughly 2.5x the cut off frequency.
Which filter you choose will depend on your application; but in general, the Butterworth filter is best for vibration and the Bessel is best for shock testing. And above all, you should avoid a system that does not offer some low pass filtering to avoid aliasing.