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This paper presents the result of research on the impulsive components of a railway noise generated during passage through a railroad switch compared with a typical rail noise and evaluation of this phenomenon with particular emphasis on impulsive sounds. The study includes the analysis of the source of impulsive components in the railway noise, the methodology of measurement and data analysis. Spectral analysis of typical fragments passing through a railroad switch is given together with a proposal of additional indicators to assess the noise. Authors propose three descriptors of the impulsive noise such as spectral centroid, kurtosis and impulsiveness, and show that these descriptors can be useful in assessment of the impulsive noise generated during trains' crossing.

Developing eective methods for automatic identication of noise sources is currently one of the most important tasks in long-term acoustical climate monitoring of the environment. Manual verication of recorded data, when it comes to proper determination of noise levels, is time-consuming and costly. A possible solution is to use pattern recognition techniques for acoustic signal recorded by a monitoring station. This paper presents usefulness of special directed measurement techniques, acoustic signal processing, and classication methods using articial intelligence (the Sammon mapping) and learning systems methods (Support Vector Machines) in the recognition of corona audible noise from ultra-high voltage AC transmission lines.

The paper deals with the analysis of possible application of neural networks technique to recognition of typical damages of UHV transmission lines. The acoustic signal generated as a result of corona effects is used as a damage symptom, as its intensity is usually increased after damage occurrence or after contamination of the surface of a conductor or an insulator string. The primary problem in the diagnostic process is the distinguishing between signals generated as results of damages and contamination's. The problem is not solved by methods based on the RF signal interference or by the classical methods of acoustic signal analysis. The construction and verification of the assumed diagnostic model have been carried out by experimental studies in laboratory conditions, where typical damages and contamination's of the transmission line elements have been simulated.

Impulse sound events are characterised by ultra high pressures and low frequencies. Lower frequency sounds are generally less attenuated over a given distance in the atmosphere than higher frequencies. Thus, impulse sounds can be heard over greater distances and will be more affected by the environment. To calculate a long-term average immission level it is necessary to apply weighting factors like the probability of the occurrence of each weather condition during the relevant time period. This means that when measuring impulse noise at a long distance it is necessary to follow environmental parameters in many points along the way sound travels and also to have a database of sound transfer functions in the long term. The paper analyses the uncertainty of immission measurement results of impulse sound from cladding and destroying explosive materials. The influence of environmental conditions on the way sound travels is the focus of this paper.