High-quality test-based models require good signal quality of the measured data. Overloads are detrimental to the signal quality. Thus, you have to make sure to spot and exclude all overloads from the data of your test-based model.
When the input signal is higher than what the data acquisition system or sensor can measure, there is an overload. There are two types of overloads that can affect your measurement:
Overloads happen in the physical domain. They are not detected if they happen outside of your maximum frequency.
Overloaded data are bad for your measurement, so you have to spot them directly while you are measuring. This is not always straightforward, so you can measure data with overloads without noticing. For this reason, you must also check your data after measuring all the excitations of each VP. Integrating this check into your measurement process ensures high-quality test-based models. (link)
You have a quantization overload when the voltage measured by the acquisition system exceeds its defined quantization range. These overloads are spotted and marked by DIRAC and automatically excluded.
AMS (Automatic Measurement Selection) excludes measurements with quantization overloads.
To avoid (or limit) quantization overloads, you must increase the quantization range. We recommend to set it to 10 V.
To change the quantization range you have to:
If sensors have a measurement range that is smaller than the quantization range, they can be overloaded before the system detects an overload. Overloaded sensors lead to bad data, so you must detect and delete them. You have to check if you get sensor overloads while measuring. However, they can be difficult to detect, so you must check the data also as soon as you finish all the measurements of a VP.
The sensors closer to the impact location are the ones that will most likely present overloads. When overloaded, the sensor channel will measure a high voltage. The signal will then slowly decrease until it reaches the zero range. The slow exponential decay of an overloaded signal in the time domain corresponds to a curve with ski-slope shape in the frequency domain, that you can visualize in the Graphing area. When a channel is overloaded, it will turn orange on the Hardware card.
To spot senor overloads while measuring:
Observe a sensor channel closest to the impact position and in the direction of the impact (driving point measurement).
When after an impact you notice that the sensor got an overload, before doing the next impact, you have to:
If you keep experiencing overloads when impacting the same spot, consider:
It could be hard to spot all sensor overloads while measuring. Once you finished measuring all FRFs of one VP, check if you missed any overload. You can spot the sensor overloads by looking at the magnitude of the FRFs in Analyze.
To spot sensor overloads in Analyze, you have to:
Sensor overloads can be recognized as offsets in the time domain and as “ski-slopes” in the frequency domain.
After spotting sensor overloads, you must delete the affected data. You then have to impact again at all excitation locations where you had overloads.
To avoid overloads you can:
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