Research On Location Model Of Airport Noise Monitoring Points

With the continuous development of China’s civil aviation industry, airport noise impact on thesurrounding environment is becoming more and more serious.In order to accurately know the noisepollution around the airport, realization of airport noise monitoring and processing system isbecoming more and more important, and the location of airport noise monitoring points is the primarytask.In order to monitor and analysis of the noise pollution near the airports, this paper proposesSANE-MinVC location model of monitoring points for small and medium-sized airports as well asMANE-PDCBR location model for large hub airports according to that the noise is sparse and scatterfor small and medium-sized airports while it is continuous and dense for large hub airports.WhenSANE-MinVC model is used, a large number of grid points are assumed as candidate monitoringpoints.These points constitute the vertex set.INM noise prediction software is used to calculate noisevalues of these vertices when each event happens.According to the noise threshold of single event, wecould determine whether a vertex monitors the event or not.Then the minimum vertex cover modelcan be established.After that, the minimum number of vertices to cover all noise events could beobtained by improving greedy algorithm.When MANE-PDCBR model is used, inflection point setshould be extracted from boundary data of areas that are affected by noise pollution.Then we shallcluster the points in the set to get their tags.After that, representatives from each cluster with largepoint density can be obtained though representative description method based on point density.Finally,we locate noise monitoring points on these representatives.Experimental results show that SANE-MinVC and MANE-PDCBR models proposed in thispaper not only overcome the defect of too many monitoring points required by grid locating method,but also make up for the lack of theoretical guidance of experience locating method.This paper makesup the cap of location research of airport noise monitoring points in China.