Measuring Exhaust Noise Using A P8000 System

The following note describes measuring exhaust noise using a Prosig P8000/DATS system for the refinement of an automotive muffler design for a major after-market exhaust manufacturer in Europe. The particular vehicle under test was required by local legislation to have an overall radiated noise level of less than 70 dB. When tested, the vehicle was found to be producing 71.8 dB of radiated noise. The design of the exhaust system clearly needed to be reviewed and modified. (more…)

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Cleaning Up Data

When we have a very noisy signal with a large number of spikes and signal bursts then if all else fails try Median Filtering. This is a technique often used in cleaning up pictures. The operation is almost childishly simple in concept but we will save the details until we have examined an example.

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Dynamic Range And Overall Level : What Are They ?

Accurate measurement of a signal depends on the dynamic range and the overall level of the data acquisition system. The overall level setting may be thought of as determining the largest signal that can be measured. This clearly depends on the present gain setting. That is the overall level is related to the gain. Clearly if the overall level is too small (gain too high) then the signal will be clipped and we will have poor quality data. The dynamic range then tells us that for the given overall level what is the smallest signal we can measure accurately whilst simultaneously measuring the large signal.

In a very simple sense suppose we have an artificial signal which consists of a sinewave at a large amplitude A for the first half and that this is followed by a sinewave with a small amplitude a for the second half. We will set the gain (the overall level) to allow the best measurement of the A sinewave. The dynamic range tells us how small a may be so we can also measure that without changing settings.
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Interpretation of the Articulation Index

The Articulation Index or AI gives a measure of the intelligibility of hearing speech in a given noise environment. The metric was originally developed in 1949 in order to give a single value that categorised the speech intelligibility of a communication system. The basic interpretation of the AI value is the higher the value then the easier it is to hear the spoken word. The AI value is expressed either as a factor in the range zero to unity or as a percentage.

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