Sound reflection measurements on noise barriers in critical conditions

• Right choice of test signal permits the measurement of noise barriers in critical conditions.
• Different results obtained using MLS or ESS depending on the type of disturbance.
• Measurements in non stationary conditions on absorbing and reflecting noise barriers.
• Broadband and impulsive background noise have been considered.
• A summary of the rules for selecting the optimal test signal is presented.

It is often necessary to check the intrinsic acoustic characteristics of installed noise barriers, like sound reflection and airborne sound insulation, to verify their compliance to design specifications or their quality after some years of life. These characteristics may be measured in-situ following CEN/TS 1793-5. These guidelines have been substantially improved in the frame of the European project QUIESST (2009–2012), which is now under consideration by the relevant CEN working groups to produce new European standards. The new method for measuring sound reflection specifies the usage of an electroacoustic sound source and a microphone grid, in order to obtain a set of impulse responses; these are processed by means of improved algorithms to compute the required results. The impulse responses are acquired using MLS (Maximum Length Sequence) or ESS (Exponential Swept-Sine) as test signals. While the acoustical characteristics of a noise barrier obtained using the two signals are generally equivalent, in critical conditions – e.g. excessive background noise or local meteorological variability – some discrepancies may occur. Moreover, different type of background noise (broadband or impulsive) give different effects on the final result, using MLS or ESS test signals. This paper presents a series of experiments designed to put in evidence the differences between Reflection Index measurements performed in the mentioned critical conditions, according to the QUIESST guidelines, done using MLS or ESS signals. The relative advantages and drawbacks are analysed and discussed in detail. Conclusions are drawn on the selection of the best test signal for each situation.