研發具邊緣運算能力之無線振動量測裝置應用於橋梁鋼索特徵頻率偵測

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Title:	研發具邊緣運算能力之無線振動量測裝置應用於橋梁鋼索特徵頻率偵測
Authors:	陳晉群;CHEN, CHIN-CHUN
Contributors:	土木工程學系
Keywords:	微振法;結構健康檢測;物聯網;邊緣運算;LoRa
Date:	2022-07-29
Issue Date:	2022-10-04 10:46:03 (UTC+8)
Publisher:	國立中央大學
Abstract:	現今橋梁健康安全檢測大多仍屬於有線傳輸，並且同一時間僅對單一或少量幾個構件進行檢測，檢測所有橋梁構件，需要伴隨大量器材設備的移動，及多次有線檢測儀器的安裝，相當的費時費力。因此本研究研發出一種無線振動量測裝置，裝置上包含了一顆微控制器 (Micro Control Unit,MCU)、一顆高精度的 ADXL355 加速度計量測鋼纜加速度、一個 LoRa(Long Range)做為無線傳輸模組、 SD 卡模組儲存實驗資料，本儀器體積大約為 15cm10cm5cm，方便攜帶、無須架設有線線材、且易安裝於鋼纜上。本研究將儀器架設在真實橋梁鋼纜上進行現地實驗，其運作模式為平常系統會維持待機狀態，當使用者發送檢測命令後，系統即開始對鋼索進行檢測，透過量測鋼纜的歷時加速度資料，並進行快速傅立葉轉換(Fast Fourier Transform, FFT)，並運行自行研發之演算法計算出鋼纜的振態頻率，透過自動化作業及無線傳輸將特徵頻率回傳給使用者，使用者即可根據弦理論推算鋼纜張力。在軟體方面，本研究克服了微控制器內存不夠影響快速傅立葉轉換資料量、與在單核心 CPU 需同時進行加速度資料採樣與儲存的問題，在特徵頻率演算法部分也提升了特徵頻率輸出的準確度。實驗結果證明了系統的可行性，成功在感測節點完成測量與運算，並成功ii 以無線傳輸方式將特徵頻率回傳給使用者，成功開發出一種可在邊緣運算且省時省力的鋼纜健康監測系統。;Nowadays, most bridge health and safety inspections are still wired transmissions, and only a single or a small number of bridge components are inspected simultaneously. The detection of all bridge components requires the movement of a large number of equipment, the installation of several wired detection instruments, and the structure of multiple wired inspection instruments, which is quite time-consuming. Therefore, this research has developed a low-power wireless vibration sensing device, which includes a micro control unit (MCU), a high-precision adxl355 acceleration meter to measure the acceleration of steel cable, and a Lora (Long range) as a wireless transmission module and SD card module to store experimental data. The volume of this instrument is about 15cm10cm5cm, which is convenient to carry and easy to install on steel cables. The operating mode is that the system will maintain a standby state. When the user sends the detection command, the system starts to detect the vibration on the steel cable. Through measuring the diachronic acceleration data of the steel cable, performing a fast Fourier transform (FFT), and running the self-developed algorithm to calculate the vibration frequency of the steel cable, the eigenfrequency is transmitted back to the user through automatic operation and wireless transmission, and the user can calculate the cable tension based on string theory. In terms of software, this study overcomes the problems of insufficient memory in the microcontroller, which affects the amount of fast Fourier transform data, and the need to sample and store acceleration data simultaneously in a single core CPU. In the eigenfrequency algorithm part, the accuracy of theiv eigenfrequency output is simultaneously experimental results that prove the system’s feasibility. The measurement and calculation are completed at the sensing node, and the eigenfrequency is transmitted back to the user by a wireless transmission system that saves time and effort.
Appears in Collections:	[Graduate Institute of Civil Engineering] Electronic Thesis & Dissertation

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