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Trend segmentation similarity-based airport noise monitoring point exception identification method

An airport noise and anomaly identification technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as data anomalies, achieve easy acquisition, improve timeliness and effectiveness, and improve accuracy and reliability Effect

Inactive Publication Date: 2017-09-15
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0005] Aiming at the problem of data anomalies in airport noise monitoring, the present invention proposes an airport noise monitoring point anomaly identification method based on trend segment similarity, so as to quickly and effectively identify abnormal noise monitoring points in a complex airport noise environment, and to Auxiliary fault location

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  • Trend segmentation similarity-based airport noise monitoring point exception identification method
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  • Trend segmentation similarity-based airport noise monitoring point exception identification method

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Embodiment Construction

[0025] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0026] The present invention is a method for abnormal identification of airport noise monitoring points based on time series similarity measurement. The process flow is as follows: figure 1 As shown, it specifically includes the following steps:

[0027] Step 1: Obtain the original time series of multiple noise monitoring points around the airport by using the noise monitoring equipment (B&K acoustic measuring instrument from Denmark) arranged around the airport;

[0028] Airport noise time series data D monitored at monitoring point i over a period of time i It can be expressed as:

[0029] D. i ={d i1 , d i2 ,...,d im}

[0030] Among them, m is the number of monitoring, d i1 is the noise value monitored at the first moment of monitoring point i in a certain period of time, d i2 is the noise value monitored by monitoring point i at the second moment, d im ...

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Abstract

The invention discloses a trend segmentation similarity-based airport noise monitoring point exception identification method and belongs to the technical field of airport noise monitoring point exception analysis. The method comprises the steps of firstly obtaining noise monitoring data of monitoring points around an airport by utilizing a monitoring device; secondly preprocessing the monitoring data and creating a standard noise time series data set; thirdly performing dimension reduction expression on noise time series of the monitoring points by using a trend segmentation-based time series expression method; fourthly by utilizing a trend segmentation-based similarity measurement method, measuring noise time series similarity between the monitoring points, and establishing a similarity matrix; fifthly finding out first k monitoring points with relatively high similarity with each monitoring point, and creating a similar monitoring point set; and finally measuring the similarity between new noise time series of the monitoring points and new noise time series of associated monitoring points, and if the similarity is remarkably changed, determining that the monitoring points are exceptional. According to the method, the monitoring point exception can be accurately identified, so that the timeliness and validity of airport noise monitoring point maintenance are effectively improved.

Description

technical field [0001] The invention discloses an airport noise monitoring point anomaly identification method based on trend segment similarity, and belongs to the technical field of airport noise monitoring point anomaly analysis. Background technique [0002] With the increasingly serious pollution of the airport noise environment and the increasing number of complaints about the impact of noise on the environment, the airport noise problem has become one of the obstacles affecting the sustainable development of the civil aviation industry. Airport noise is mainly the noise generated when aircraft take off, land, ascend, descend and other important operations in civil aviation airports, which will have some negative impacts on the airport, especially the surrounding environment. Airport noise monitoring is not only a requirement of national and local laws and regulations for airport management agencies, but also helps airport authorities understand the impact and scope of...

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 陈海燕刘晨晖谢华
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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