本文選題：旋轉(zhuǎn)機(jī)械 + 振動(dòng)監(jiān)測(cè)　； 參考：《北京化工大學(xué)》2012年碩士論文

【摘要】：本文來源于國家自然科學(xué)基金項(xiàng)目—機(jī)械故障無線傳感網(wǎng)絡(luò)監(jiān)測(cè)與智能診斷方法研究（51075023）。 旋轉(zhuǎn)機(jī)械設(shè)備是現(xiàn)今工業(yè)生產(chǎn)系統(tǒng)的重要組成部分，其運(yùn)行狀態(tài)對(duì)生產(chǎn)系統(tǒng)的穩(wěn)定性及安全性有著直接影響，設(shè)計(jì)高效的旋轉(zhuǎn)機(jī)械振動(dòng)監(jiān)測(cè)裝置對(duì)于防止故障發(fā)生有著重大的實(shí)際意義。目前針對(duì)旋轉(zhuǎn)機(jī)械的監(jiān)測(cè)方案主要為基于專家系統(tǒng)的在線監(jiān)測(cè)方式和基于便攜式終端的人工巡檢方式，，前者的振動(dòng)信號(hào)采集點(diǎn)數(shù)據(jù)處理能力有限，主要依賴于大數(shù)據(jù)量的振動(dòng)信號(hào)上傳，因此對(duì)數(shù)據(jù)傳輸帶寬及相應(yīng)的線路配置要求較高，而后者受制于專業(yè)人員的檢查方式且難以實(shí)現(xiàn)不間斷監(jiān)測(cè)。本文自主設(shè)計(jì)的基于ARM的嵌入式RTAI+Linux智能數(shù)據(jù)采集平臺(tái)彌補(bǔ)了現(xiàn)有監(jiān)測(cè)方式的不足，通過加載監(jiān)測(cè)診斷算法能夠準(zhǔn)確地對(duì)采集的振動(dòng)信號(hào)進(jìn)行狀態(tài)識(shí)別和初步故障診斷，從而提高了信號(hào)采集端的數(shù)據(jù)處理和識(shí)別能力，并且可加載無線數(shù)據(jù)傳輸模塊將監(jiān)測(cè)結(jié)果或故障數(shù)據(jù)通過無線網(wǎng)絡(luò)傳輸?shù)缴衔粰C(jī)，從而彌補(bǔ)了人工巡查和有線傳輸?shù)牟蛔恪?本文自主設(shè)計(jì)的嵌入式RTAI+Linux智能數(shù)據(jù)采集平臺(tái)主要由智能雙模傳感器、信號(hào)預(yù)處理、數(shù)據(jù)處理和傳輸?shù)炔糠纸M成。本文提出了一種自適應(yīng)選擇較優(yōu)振動(dòng)信號(hào)的雙模傳感器設(shè)計(jì)方案，并完成了其硬件設(shè)計(jì)和研制，該雙模傳感器由兩種不同測(cè)量范圍和精度的加速度傳感器組成，采集平臺(tái)能夠在滿足量程的基礎(chǔ)上動(dòng)態(tài)選擇較高測(cè)量精度的信號(hào)；完成了以ARM為核心的數(shù)據(jù)采集平臺(tái)硬件設(shè)計(jì)，該平臺(tái)采用嵌入式RTAI+Linux雙內(nèi)核結(jié)構(gòu)，此模式下設(shè)計(jì)的底層驅(qū)動(dòng)程序和應(yīng)用程序能夠更實(shí)時(shí)高效地對(duì)硬件請(qǐng)求和中斷進(jìn)行響應(yīng)，從而提高底層數(shù)據(jù)通信和處理效率；智能數(shù)據(jù)采集平臺(tái)能夠通過加載的監(jiān)測(cè)診斷算法對(duì)振動(dòng)信號(hào)進(jìn)行狀態(tài)特征提取和異常診斷，依據(jù)設(shè)備狀態(tài)分別將特征參數(shù)或振動(dòng)波形數(shù)據(jù)傳至監(jiān)測(cè)系統(tǒng)數(shù)據(jù)服務(wù)器。 最后將智能數(shù)據(jù)采集平臺(tái)用于振動(dòng)實(shí)驗(yàn)臺(tái)滾動(dòng)軸承監(jiān)測(cè)，實(shí)驗(yàn)證明其能夠?qū)崿F(xiàn)振動(dòng)信號(hào)的采集、信號(hào)的特征參數(shù)提取以及軸承狀態(tài)的簡易識(shí)別，并能夠?qū)⑻卣鲄?shù)和故障波形數(shù)據(jù)傳至服務(wù)器。該平臺(tái)的構(gòu)建為實(shí)現(xiàn)整個(gè)設(shè)備的無線監(jiān)測(cè)系統(tǒng)提供了技術(shù)基礎(chǔ)。
[Abstract]:This paper comes from the project of National Natural Science Foundation of China-Research on Monitoring and Intelligent diagnosis method of Mechanical Fault Wireless Sensor Network. Rotating machinery is an important part of industrial production system. Its running state has a direct impact on the stability and safety of the production system. It is of great practical significance to design an efficient vibration monitoring device for rotating machinery to prevent the occurrence of faults. At present, the monitoring schemes for rotating machinery are mainly based on the online monitoring mode based on expert system and the manual inspection mode based on portable terminal. The former has limited data processing ability of vibration signal acquisition points. It mainly depends on the vibration signal upload of large amount of data, so the data transmission bandwidth and the corresponding line configuration are very high, and the latter is restricted by the inspection way of the professionals and it is difficult to realize the continuous monitoring. The embedded RTAI Linux intelligent data acquisition platform based on arm is designed in this paper to make up for the deficiency of the existing monitoring methods. By loading the monitoring and diagnosis algorithm, we can accurately identify the state of the collected vibration signal and diagnose the initial fault. Thus, the data processing and recognition ability of the signal acquisition terminal is improved, and the wireless data transmission module can be loaded to transmit the monitoring results or fault data to the upper computer through the wireless network. The embedded RTAI Linux intelligent data acquisition platform is mainly composed of intelligent dual-mode sensor, signal preprocessing, data processing and transmission. In this paper, a design scheme of a dual-mode sensor which adaptively selects a better vibration signal is proposed, and its hardware design and development are completed. The dual-mode sensor is composed of two accelerometers with different measuring range and precision. The acquisition platform can dynamically select the signal with high measurement precision on the basis of satisfying the range, and complete the hardware design of the data acquisition platform with arm as the core. The platform adopts the embedded RTAI Linux dual kernel structure. The underlying drivers and applications designed in this mode can respond to hardware requests and interrupts more efficiently in real time so as to improve the communication and processing efficiency of the underlying data. The intelligent data acquisition platform can extract the state feature and diagnose the abnormal of vibration signal through the loaded monitoring and diagnosis algorithm. According to the state of the equipment, the characteristic parameters or the vibration waveform data are transferred to the data server of the monitoring system respectively. Finally, the intelligent data acquisition platform is used in the rolling bearing monitoring of the vibration test bench, which is proved to be able to collect the vibration signals. The feature parameters of the signal are extracted and the bearing state can be easily identified, and the characteristic parameters and fault waveform data can be transmitted to the server. The construction of the platform provides the technical foundation for the wireless monitoring system of the whole equipment.
【學(xué)位授予單位】：北京化工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TH165.3;TP274

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 趙斌,喬桂紅,吳錫鵬;汽輪發(fā)電機(jī)組振動(dòng)故障診斷方法研究[J];東北電力學(xué)院學(xué)報(bào);2005年04期

2 王永成;黨源源;徐抒巖;王國輝;;基于CPLD實(shí)現(xiàn)DSP的UART設(shè)計(jì)研究[J];電子器件;2008年03期

3 鄧曉云;基于振動(dòng)診斷技術(shù)的曲軸主軸頸磨床故障診斷[J];大連鐵道學(xué)院學(xué)報(bào);2005年01期

4 張?jiān)谛?康素坤;張新;;淺析振動(dòng)分析技術(shù)在旋轉(zhuǎn)機(jī)械設(shè)備故障診斷中的應(yīng)用[J];硅谷;2009年10期

5 張?jiān)品?李健;DPCM-based vibration sensor data compression and its effect on structural system identification[J];Earthquake Engineering and Engineering Vibration;2005年01期

6 張琳,朱瑞松,尤一匡,尤侯平,王正洪;往復(fù)壓縮機(jī)監(jiān)測(cè)與診斷技術(shù)研究現(xiàn)狀與展望[J];化工進(jìn)展;2004年10期

7 曾儒偉,許誠,曾亮;故障診斷方法發(fā)展動(dòng)向[J];航空計(jì)算技術(shù);2003年03期

8 李小群,趙慧斌,葉以民,孫玉芳;一種基于時(shí)鐘粒度細(xì)化的Linux實(shí)時(shí)化方案[J];計(jì)算機(jī)研究與發(fā)展;2003年05期

9 李程遠(yuǎn),劉文峰,李善平;ARM Linux在EP7312上的移植[J];計(jì)算機(jī)工程與設(shè)計(jì);2003年07期

10 朱紅星;苗克堅(jiān);;Linux下PCI設(shè)備流式DMA驅(qū)動(dòng)開發(fā)[J];微處理機(jī);2007年04期

相關(guān)博士學(xué)位論文 前1條

1 耿俊豹;基于信息融合的艦船動(dòng)力裝置技術(shù)狀態(tài)綜合評(píng)估研究[D];華中科技大學(xué);2007年

相關(guān)碩士學(xué)位論文 前10條

1 許勇;基于ZigBee的Mesh網(wǎng)絡(luò)的研究[D];中國科學(xué)技術(shù)大學(xué);2011年

2 韓宏宇;基于FPGA的風(fēng)電監(jiān)測(cè)系統(tǒng)數(shù)據(jù)采集單元設(shè)計(jì)[D];北京化工大學(xué);2011年

3 李江偉;便攜式大型旋轉(zhuǎn)機(jī)械故障診斷系統(tǒng)[D];廣東工業(yè)大學(xué);2002年

4 涂曉峰;基于嵌入式Linux智能儀器系統(tǒng)與USB通信實(shí)現(xiàn)研究[D];浙江大學(xué);2004年

5 周丹;一種改進(jìn)型的硬實(shí)時(shí)調(diào)度算法在RTLinux上的設(shè)計(jì)與實(shí)現(xiàn)[D];西南交通大學(xué);2005年

6 馮峰;嵌入式Linux操作系統(tǒng)的實(shí)現(xiàn)及其應(yīng)用研究[D];西南交通大學(xué);2005年

7 孫楠楠;大型旋轉(zhuǎn)機(jī)械振動(dòng)監(jiān)測(cè)與故障診斷知識(shí)體系的研究與實(shí)現(xiàn)[D];重慶大學(xué);2006年

8 胡志偉;嵌入式實(shí)時(shí)仿真測(cè)試平臺(tái)研究[D];國防科學(xué)技術(shù)大學(xué);2007年

9 李華軍;基于RTLinux的車輛檢測(cè)系統(tǒng)研究與實(shí)現(xiàn)[D];電子科技大學(xué);2008年

10 萬奇云;基于Intel XScale架構(gòu)Linux系統(tǒng)移植[D];華中科技大學(xué);2007年

本文編號(hào)：1987276