Due to the high impact of the presence of noise in industry, it is mandatory to reduce acoustic noise hazard below the limit where risk to hearing occurs. The first step to achieve this is the identification of acoustic noise sources, which is a complex task that can be achieved using a wide range of techniques that involve different technologies for sound data acquisition, signal processing and study of physical construction. Sound source localization techniques fall into three standard categories: near-field acoustic holography, acoustic beam-forming and inverse methods. Selecting one method or another depends on the test object, nature of the sound, and the actual environment. In this paper, an intelligent system in the form of a microphone array based on a beam-forming method is proposed for noise detection and localization in porous panel structures through wind tunnel tests. The modification of an already existing experiment by the inclusion of new intelligent entities will increase the scope of these kinds of studies. Strengthening the communication level between the units involves assuring a more accurate identification of the noise sources and consequently assists in undertaking proper action to mitigate them.