User manual

Sound Level Meter

Events (optional)

The event function is available with the XL2 Extended Acoustic

Pack Option. The XL2 Analyzer may be conﬁgured to record

wav-ﬁles and additional noise levels only when triggered, in-

stead of the complete measurement duration.

Advantages

Reduces the data volume acquired, thereby

Simplifying data post-processing•

Saving memory for long-term measurement applications.•

Events

Events are triggered either automatically by sound levels above/

below a preset value or manually by external key press using

the XL2 Input Keypad.

Data Logging

The XL2 Analyzer logs the data speciﬁed in the

LOG setting for the complete measurement du-

ration into a log ﬁle. The markers and triggered

events results are added to the same log ﬁle.

The XL2 Input Keypad is available as an acces-

sory. Please see chapter Options and Accesso-

ries for details.

Recommendation

With the large storage capacity of the XL2, NTi Audio recom-

mends logging at a 1 second or faster interval. This allows the

accurate collection of event data; one event will be stored with-

in a logged interval. If results for reporting are required at lon-

ger intervals, e.g. one hour, the XL2 Data Explorer software is

recommended. It easily combines logged data into longer audit

intervals. An additional advantage of a faster logging interval is

that only an entire logged interval can be excluded from the

average. This is useful when a qualiﬁed noise consultant judges

that a sound is not caused by the object under test or is not a

normal sound for a measurement location.

Functions

The XL2 event feature offers the following functionalities:

Automated event triggered at noise levels above/below a •

preset value including setting markers for speciﬁc noise cat-

egories. Application example: Recording the noise level for

> 80 dB.

Event triggered by external key press of the XL2 Input Key-•

pad. You can utilize four keys (1-4) to categorize any noise of

interest or noise to be later excluded in the post-processing.

A typical application is categorizing any annoying industrial

noise by persons living in the neighborhood.