Signal processing method of wireless anemobiagraph

Abstract

The invention discloses a signal processing method of a wireless anemobiagraph, which comprises the steps of: analyzing signals in a certain time interval according to a wind speed and a wind direction in the signals subjected to A/D (Analog-to-Digital) conversion by the wireless anemobiagraph, calculating a horizontal average wind speed, a horizontal average wind direction, a vertical average wind speed, a vertical average wind direction as well as turbulence intensities, gust factors, turbulence integral scales and fluctuating wind power spectrums in a down wind direction, a horizontal wind direction and a vertical wind direction; fitting the fluctuating wind power spectrums in the horizontal wind direction and the vertical wind direction by adopting a Kaimal spectrum and a Panofsky spectrum to obtain a coefficient of a power spectrum density function; and storing a calculating result to a data storage of the wireless anemobiagraph, and compiling all relevant embedded calculating programs. According to the invention, demands of signal characteristics and wind load analysis of the wireless anemobiagraph are fully considered, automatic calculation of wind filed characteristic parameters is realized in the wireless anemobiagraph, and data transmission quantity of the wireless anemobiagraph and later stage analysis workload of the wind load data are greatly reduced.

Description

technical field [0001] The invention relates to a signal processing method, in particular to a signal processing method after A / D conversion of a wireless anemometer, which is mainly used in the field of civil engineering bridge or structural health monitoring. Background technique [0002] Wind load is one of the main loads of long-span bridge structures. Using the field measured wind field characteristic data in the bridge area to analyze the structure is a commonly used structural wind engineering research method. Through the on-site measurement of the wind field in the bridge site area by the anemometer, the characteristic parameters of the wind field in the bridge site area can be obtained, mainly including the average wind characteristics (average wind speed, average wind direction, variation of wind speed with height, etc.) and fluctuating wind characteristics (turbulent flow intensity, gust factor, turbulence integration scale, power spectral density function, etc.)....

AI Technical Summary

Problems solved by technology

This processing method often takes a lot of time, and the data processing efficiency is also low. It cannot achieve the real-time performance of the test results, and cannot correct the instrument problems and signal problems in the test process in time.

Especially for the wind speed test of the structural health monitoring system, the centralized data processing takes a lot of time, and the damage of the structure under strong wind often occurs in an extreme time, so the wind load early warning ability of the structural health monitoring system is limited

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