Automatic cloud signal recognition method based on finite-state machine

A finite state machine and automatic identification technology, applied in the field of spectral analysis, can solve the problems of large amount of calculation and low precision of cloud finding

Inactive Publication Date: 2017-01-04
安徽安光环境科技有限公司
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Problems solved by technology

[0004] The object of the present invention is to provide a kind of cloud layer signal automatic identification method based on finite state machine, has realized the accurate se

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  • Automatic cloud signal recognition method based on finite-state machine
  • Automatic cloud signal recognition method based on finite-state machine
  • Automatic cloud signal recognition method based on finite-state machine

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[0030] In order to make the objectives, technical solutions, and advantages of the present invention clearer and clearer, the present invention will be further described in detail below in conjunction with specific implementation cases and with reference to the accompanying drawings.

[0031] Such as figure 1 It is a schematic diagram of a laser cloud measurement system, including a laser emitting unit, a signal detecting unit, and a signal receiving unit.

[0032] Such as Figure 2-5 , An automatic recognition method of cloud signals based on finite state machine, mainly includes the following steps:

[0033] (1) Collect the original signal data by the ceilometer, the original signal data of the ceilometer including a series of increased distance values ​​and the corresponding signal intensity at each distance;

[0034] (2) The average value of the original signal above a certain height of the ceilometer is taken as the background value of the original signal of the ceilometer, and t...

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Abstract

The invention discloses an automatic cloud signal recognition method based on a finite-state machine. According to the method, basic characteristics of the cloud signals are generalized into cloud base, cloud peak, cloud top and public boundary of two clouds according to the whole characteristics of the cloud signals; ceilometer signals can be separately chosen out by encoding ceilometer echo signals into cloud signal description sentences. The method comprises the steps that the cloud signals and related inversion parameters are smoothly filtered, and a first-order derivative of the echo signals is obtained; then the cloud base, the cloud peak, the cloud top and the public boundary of the two clouds are encoded into the cloud signal description sentences; the situation that the signals of rain, fog and peak interference are judged as the cloud signal in error is avoided by recognizing and logically analyzing the characteristics of the cloud signals; positions of the cloud base, the cloud peak and the cloud top in a cloud layer can be given out. The method can meet the situation of recognizing three layers of clouds to the maximum degree and improves the cloud signal recognition success rate.

Description

Technical field [0001] The invention belongs to the technical field of spectral analysis, and specifically relates to a method for automatically identifying cloud signals based on a finite state machine, which is mainly applied to the automatic identification of cloud signals in the atmosphere and the automatic output of the positions of cloud bottom, cloud peak and cloud top. Background technique [0002] In the current meteorological business observations, cloud observation is an important item. The observation method mainly relies on manual observation, but manual observation has disadvantages such as strong subjectivity and poor accuracy. Therefore, the China Meteorological Administration has considered using laser clouds. GROHE replaces manual observation. The existing cloud height inversion algorithms based on ceilometer or lidar mainly include differential zero-crossing method, Klett method, sliding window integration method, etc., but these inversion algorithms are relati...

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Application Information

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IPC IPC(8): G01S17/95
CPCG01S17/95Y02A90/10
Inventor 付强钱江张帅贺文干
Owner 安徽安光环境科技有限公司
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