發(fā)布時間：2018-06-19 16:50

  本文選題：數(shù)字信號處理 + 磨粒監(jiān)測�。� 參考：《北京交通大學》2017年碩士論文

【摘要】：摘要:在風力發(fā)電機運行過程中,其內(nèi)部的部件會相互接觸摩擦產(chǎn)生磨損顆粒,這些磨粒隨著潤滑油在油路中循環(huán)。通過監(jiān)測風力發(fā)電機油液中的磨粒信息可以確定合適的換油時機以及判斷風力發(fā)電機的磨損程度,從而增加風力發(fā)電機的安全性及延長其使用壽命。本文針對磨粒信號檢測存在的難點,提出了磨粒信號檢測算法,研究并設(shè)計了一套風機油液磨粒在線監(jiān)測系統(tǒng),實現(xiàn)對風力發(fā)電機油液中的磨粒在線監(jiān)測。本文研究的對象為風機油液磨粒在線監(jiān)測系統(tǒng),分別從系統(tǒng)的設(shè)計需求、磨粒信號檢測算法、系統(tǒng)的總體設(shè)計三個方面展開研究。(1)提出了風機油液磨粒在線監(jiān)測系統(tǒng)的總體設(shè)計框架,由磨粒傳感器、磨粒信號數(shù)據(jù)處理、上位機三部分組成。磨粒信號數(shù)據(jù)處理部分需要具備對磨粒數(shù)據(jù)的采集、數(shù)據(jù)處理、數(shù)據(jù)存儲、數(shù)據(jù)通信等功能,根據(jù)各項功能,提出相應的方法策略,并根據(jù)系統(tǒng)設(shè)計的需求進行選擇。(2)分析了磨粒信號檢測存在的難點,主要包括高頻信號干擾、基線漂移、尖峰干擾、慣性假峰、波形截斷等問題,這些問題的存在會造成磨粒多檢和漏檢。利用多項式擬合移動平滑濾波算法對信號進行濾波,消除高頻信號干擾;利用尋峰算法解決基線漂移、尖峰干擾、慣性假峰的問題,從采樣信號中尋找到磨粒波形的波峰和波谷;提出兩類分類算法解決波形截斷的問題,根據(jù)波峰和波谷的信息對磨粒信號分類,提取出真實磨粒數(shù)據(jù)信息。(3)從軟件和硬件上設(shè)計并實現(xiàn)了風機油液磨粒在線監(jiān)測系統(tǒng)。在軟件上,實現(xiàn)了通過DMA的方式搬移采樣數(shù)據(jù)、利用I2C總線將數(shù)據(jù)存儲進鐵電存儲器中、通過Modbus通信協(xié)議實現(xiàn)與上位機的通信等功能;硬件方面,設(shè)計了以DSP為核心的系統(tǒng)硬件電路。本文通過實驗對磨粒信號檢測算法中的參數(shù)進行設(shè)置、通過數(shù)據(jù)連續(xù)性測驗驗證了 DMA搬移數(shù)據(jù)的可行性、通過濾波測試驗證了濾波算法的有效性、通過磨粒檢測實驗驗證了磨粒檢測算法對于直徑大于100μm的鐵磁磨粒和直徑大于500μm的非鐵磁磨粒具有較好的檢測效果、通過上位機監(jiān)測的結(jié)果驗證了整個系統(tǒng)的有效性。
[Abstract]:Absrtact: during the operation of wind turbine, the internal components of wind turbine will contact each other to produce wear particles, which circulate in the oil circuit with lubricating oil. By monitoring the information of abrasive particles in the oil of wind turbine, we can determine the right time of oil exchange and judge the degree of wear of wind turbine, so as to increase the safety of wind turbine and prolong its service life. Aiming at the difficulties in the signal detection of abrasive particles, this paper puts forward an algorithm for detecting the signal of abrasive particles, studies and designs a set of on-line monitoring system of wear particles in fan oil, which can realize the on-line monitoring of abrasive particles in the oil of wind turbine. The object of this paper is the on-line monitoring system of oil abrasive particles in fan, which is based on the design requirements of the system, the signal detection algorithm of abrasive particles, The overall design framework of the on-line monitoring system for oil abrasive particles in fan is proposed, which consists of three parts: abrasive particle sensor, abrasive particle signal data processing and upper computer. The data processing part of abrasive particle signal needs to have the functions of collecting, processing, storing, communicating and so on. According to each function, the corresponding method and strategy are put forward. According to the requirements of the system design, the paper analyzes the difficulties of the wear particle signal detection, including high frequency signal interference, baseline drift, spike interference, inertia false peak, waveform truncation and so on. The existence of these problems will result in multiple detection and missed detection of abrasive particles. The polynomial fitting moving smoothing filter algorithm is used to filter the signal to eliminate the high frequency signal interference, and the peak seeking algorithm is used to solve the problems of baseline drift, peak interference and inertial false peak. Two kinds of classification algorithms are proposed to solve the problem of waveform truncation. According to the information of wave peak and trough, the wear particle signal is classified. The real abrasive particle data information is extracted. The on-line monitoring system of fan oil abrasive particles is designed and implemented from the software and hardware. In software, the data is moved by DMA, the data is stored in ferroelectric memory by I2C bus, and the communication with host computer is realized by Modbus protocol. The system hardware circuit based on DSP is designed. In this paper, the parameters of abrasive signal detection algorithm are set through experiments, the feasibility of DMA moving data is verified by data continuity test, and the validity of filtering algorithm is verified by filter test. The testing results show that the algorithm is effective for ferromagnetic abrasive particles with diameter greater than 100 渭 m and non-ferromagnetic abrasive particles with diameter greater than 500 渭 m, and the effectiveness of the whole system is verified by the monitoring results of upper computer.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM315

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本文編號：2040540