Airport noise event recognition method based on time series kernel clustering

Abstract

The invention discloses an airport noise event recognition method based on a time series kernel clustering, and belongs to the airport noise recognition field. This method comprises the following steps of: acquiring a raw monitoring time series of airport noise; pre-processing the raw monitoring time series, creating a noise time series data set; using a k-means clustering method based on an overall alignment kernel to automatically classify the noise time series data set and to get multiple clustering results through cycles; adding a noise event category label corresponding to each type of the noise time series in the multiple clustering results; creating a noise event knowledge base; and finally carrying out the noise event recognition to the noise time series to be recognized according to the knowledge base. The method of the invention has a high degree of intelligence, and effectively improves the efficiency and accuracy of the airport noise event recognition.

Description

technical field [0001] The invention relates to an airport noise identification method, in particular to an airport noise event identification method based on time series kernel clustering, and belongs to the field of airport noise event identification in airport noise monitoring technology. Background technique [0002] With the development of our country's social economy, airports have become the main symbol of modern cities. However, while airports provide fast and convenient transportation for passengers and goods, they also bring about noise pollution. At present, airport noise has become one of the problems in the prevention and control of urban environmental noise. [0003] Developed countries, regions and relevant international organizations have begun to pay attention to the problem of airport noise pollution as early as the 1960s. Developed countries have attached great importance to the problem of airport noise and promulgated numerous standards and regulations. ...

AI Technical Summary

Problems solved by technology

However, the current research literature on airport noise event identification is very scarce. Some existing noise identification methods are for specific mechanical equipment to identify the noise source. These methods are mainly based on the frequency domain data of the noise signal and obtained Corresponding noise frequency data, and then analyze the frequency characteristics of these noises to identify the noise source

This type of method has poor adaptability and needs to analyze and identify noise in an ideal environment. However, the noise around the airport is complex and changeable. It is difficult for traditional methods to be effectively applied in such high-noise real scenes, so the accuracy rate is very low.

In addition, the analysis efficiency of traditional methods is low. For the airport environment where noise events occur frequently, more efficient identification methods are needed to identify noise events.

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