本文關(guān)鍵詞： 希爾伯特-黃變換 狀態(tài)監(jiān)測 LabVIEW 諧波信號分析　出處：《昆明理工大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：機(jī)械設(shè)備的故障監(jiān)測是工業(yè)生產(chǎn)中重要的一個問題,目前對機(jī)械故障的判斷較多都是人為判斷,這樣不僅影響工業(yè)生產(chǎn)效益,也不能及時對機(jī)械故障進(jìn)行排查,嚴(yán)重的甚至導(dǎo)致停產(chǎn)及人員傷亡,因此,設(shè)計出一套完善的機(jī)械設(shè)備狀態(tài)監(jiān)測系統(tǒng)對工業(yè)生產(chǎn)非常重要,這套系統(tǒng)不僅要能準(zhǔn)確判斷出機(jī)械是否出現(xiàn)故障,而且在及時性和實(shí)時性上都有很高的要求,這樣才能保證將機(jī)械故障造成的損失減少到最小 本文主要針對常見的機(jī)械信號進(jìn)行仿真分析研究,基于虛擬儀器平臺設(shè)計出一種新型可通用的機(jī)械故障狀態(tài)監(jiān)測分析系統(tǒng)。本系統(tǒng)是在LabVIEW平臺上應(yīng)用希爾伯特-黃(Hilbert-Huang,HHT)變換方法,對仿真機(jī)械故障中的振動試驗(yàn)數(shù)據(jù)進(jìn)行時頻聯(lián)合分析(Joint Time-Frequency Analysis,JTFA),得出具體分析圖。 本文的主要工作如下： 1)首先,利用LabVIEW平臺的虛擬示波器產(chǎn)生諧波對系統(tǒng)進(jìn)行驗(yàn)證,得證本系統(tǒng)的正確性和可靠性；再通過一套數(shù)據(jù)采集系統(tǒng)對數(shù)據(jù)進(jìn)行實(shí)際采集,加以分析處理,得出本系統(tǒng)的可實(shí)施性。其中,數(shù)據(jù)采集系統(tǒng)主要采用NI公司設(shè)計的PCI-6251數(shù)據(jù)采集板卡和SC-7025面包板；在信號預(yù)處理方面,本文設(shè)計了數(shù)字濾波器和小波降噪儀對信號進(jìn)行濾波與去噪； 2)此外,為了對比正常信號與故障信號,進(jìn)一步提高了信號分析的準(zhǔn)確性,加入了數(shù)據(jù)存儲與讀取系統(tǒng),從而為研究機(jī)械故障提供參考圖形數(shù)據(jù)。 3)最終,本文獨(dú)自設(shè)計的HHT算法分析系統(tǒng)可以對振動信號進(jìn)行分析,從而判斷常見的機(jī)械故障,體現(xiàn)本系統(tǒng)的實(shí)用性與普遍性。 本文的目的主要是對希爾伯特黃變換的理解和應(yīng)用,不僅對此算法提出改進(jìn)方法,而且把時頻聯(lián)合分析法中最新的研究——HHT算法變換與虛擬儀器中的佼佼者——LabVIEW軟件很好的結(jié)合起來,在信號輸入的準(zhǔn)確率高、及時性好和穩(wěn)定性強(qiáng)的基礎(chǔ)上,實(shí)現(xiàn)對數(shù)據(jù)完善的處理和分析,盡量減少負(fù)面影響,達(dá)到故障診斷的最佳判斷。 本文研究得證,HHT算法能在LabVIEW上得到很好地實(shí)現(xiàn),并且信號分析結(jié)果很好,能夠獲得預(yù)期的波形和數(shù)據(jù),這樣為今后的實(shí)際應(yīng)用做好了準(zhǔn)備。
[Abstract]:The fault monitoring of machinery and equipment is an important problem in industrial production. At present, the judgment of mechanical fault is mostly artificial judgment, which not only affects the efficiency of industrial production, but also can not investigate the mechanical fault in time. It is very important to design a perfect monitoring system for the condition of machinery and equipment. This system should not only accurately judge whether the machinery is out of order or not. Moreover, there are high requirements in timeliness and real-time, so that the loss caused by mechanical failure can be minimized. In this paper, the common mechanical signals are simulated and analyzed. Based on the virtual instrument platform, a new general-purpose mechanical fault condition monitoring and analysis system is designed. The system is based on the LabVIEW platform and is applied to Hilbert-Huang. In this paper, the time-frequency joint Time-Frequency analysis method is used to analyze the vibration test data in simulated mechanical faults. The concrete analysis diagram is obtained. The main work of this paper is as follows: 1) first of all, using the virtual oscilloscope of LabVIEW platform to produce harmonics to verify the correctness and reliability of the system; Then through a set of data acquisition system to collect the actual data, to analyze and process, get the implementation of the system. The data acquisition system mainly adopts PCI-6251 data acquisition board and SC-7025 bread board designed by NI company. In the aspect of signal preprocessing, digital filter and wavelet denoising instrument are designed to filter and Denoise the signal. 2) in order to further improve the accuracy of signal analysis, a data storage and reading system is added to provide reference graphic data for the study of mechanical faults. 3) finally, the HHT algorithm analysis system designed in this paper can analyze the vibration signal and judge the common mechanical fault, which reflects the practicability and universality of the system. The purpose of this paper is to understand and apply Hilbert-Huang transform, not only to improve the algorithm. And the latest research in the joint time-frequency analysis, HHT algorithm transformation and the outstanding virtual instruments-LabVIEW software very good combination, in the signal input accuracy. On the basis of good timeliness and strong stability, the processing and analysis of the data is perfect, the negative influence is reduced as far as possible, and the best judgment of fault diagnosis is achieved. In this paper, we find that the HHT algorithm can be well implemented on LabVIEW, and the signal analysis results are very good, and can obtain the expected waveform and data. In this way, preparation is made for the practical application in the future.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TH165.3

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