１． Purpose

The S-255 model has the ability to speedily detect low level rub and buzz noise. The rub and buzz detection extracts noise elements by the subsequent mechanisms

(1) Noise is differentiated from the main signals by employing the fact that noise appears as high harmonic components of driving signals of speakers.

(2) noise is removed by adopting the idea that rub and buzz noise is composed of constituents that have correlation with driving signals. The combination makes the tool exceptionally superior in detecting rub and buzz noise, and being noise resistant as well as verifying good/defective samples objectively. Thus ETANI has been promoting this ability for more than 20 years.

(2) is an automatic mechanism, so there is no need to set up. But in (1), the harmonic distortion that occurs in normal speakers, and the high harmonic components generated by rub and buzz, are separated by a high pass filter with a cutoff frequency that varies according to the fundamental wave and tracking.

Therefore, how effectively the high pass filter is set up in order to differentiate the rub and buzz noise, becomes the key to utilizing this tool.

Here, the Rub & Buzz Analysis Tool has been developed to observe this. It provides:

• Enhanced Measurement Software: Digitally records sound extracted by a measurement microphone.
• Sonar Graph: Analyzes frequencies of recorded sound. Shows the differences between components of good/defective sound. Displays the changing sweep sound over time in a time vs. frequency view.

On the basis of analyzed results by Sonar Graph, you set up the cut-off frequency of high pass filter as follows:

• Exclude distortion components that appear in good samples from filter components.
• Define a cutoff frequency so that only what is recognized as noise passes through.

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２. How to Use S-255 Rub & Buzz Analysis Tool

Use the tool as follows:

• Prepare good and defective samples, and measure using the S-255.
• Save wave data to a file when testing.
• Load saved wave data to the Sonar Graph. Examine data and set the filter constants. If necessary, open sonar graph screens of different samples and compare them to consider the filter constants.