本文關(guān)鍵詞：機(jī)械密封端面狀態(tài)監(jiān)測(cè)及壽命預(yù)測(cè)關(guān)鍵技術(shù)研究　出處：《西南交通大學(xué)》2015年博士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 機(jī)械密封 狀態(tài)監(jiān)測(cè) 聲發(fā)射 Laplace小波 HSSVM BFHMM

【摘要】：機(jī)械密封(Mechanical Seal,MS)是反應(yīng)釜、離心泵、壓縮機(jī)和渦輪機(jī)等機(jī)械裝置的組成部件,用于旋轉(zhuǎn)設(shè)備防止泄露、節(jié)約能源和保護(hù)環(huán)境等。如果把反應(yīng)釜、離心泵、壓縮機(jī)和渦輪機(jī)等看做一個(gè)動(dòng)力系統(tǒng)的心臟,那么機(jī)械密封就相當(dāng)于這顆心臟的瓣膜。機(jī)械密封狀態(tài)監(jiān)測(cè)(Mechanical Seal Condition Monitoring,MSCM)的目的在于掌握密封設(shè)備發(fā)生故障之前的異常信息與劣化征兆,以便工程人員事前采取針對(duì)性措施防止故障的發(fā)生或降低其發(fā)生的可能性,從而減少因故障所導(dǎo)致的停機(jī)時(shí)間和因停機(jī)而造成的所有損失,最終降低企業(yè)維修費(fèi)用并提高設(shè)備的有效利用率。本文在深入探討國(guó)內(nèi)外機(jī)械密封狀態(tài)監(jiān)測(cè)研究現(xiàn)狀的基礎(chǔ)上,通過(guò)多傳感器監(jiān)測(cè)實(shí)驗(yàn)對(duì)機(jī)械密封端面狀態(tài)進(jìn)行了進(jìn)一步的研究分析,其主要內(nèi)容如下：(1)機(jī)械密封端面一方面要接觸緊密以防止流體泄露；而另一方面密封端面間隙又不能過(guò)小,以防止端面過(guò)度接觸而損傷密封端面。為了保障機(jī)械密封低摩擦和小泄露量的兼容和平衡,首先須對(duì)設(shè)備運(yùn)轉(zhuǎn)時(shí)密封端面開(kāi)啟轉(zhuǎn)速進(jìn)行檢測(cè)。由于聲發(fā)射信號(hào)對(duì)機(jī)械密封端面接觸狀態(tài)具有很好的直接反饋性,而且雙邊Laplace小波能夠很好地提取聲發(fā)射信號(hào)中的脈沖性,提出基于聲發(fā)射信號(hào)的雙邊非對(duì)稱(chēng)Laplace小波相關(guān)系數(shù)法用來(lái)檢測(cè)機(jī)械密封端面開(kāi)啟轉(zhuǎn)速。(2)機(jī)械密封端面接觸狀態(tài)直接影響著密封裝置性能和使用壽命,因而對(duì)機(jī)械密封端面摩擦狀態(tài)的監(jiān)測(cè)非常必要。由于聲發(fā)射信號(hào)頻譜受主軸轉(zhuǎn)速影響非常小,研究了基于聲發(fā)射信號(hào)利用超球面支持向量機(jī)(Hyper-Sphere Support Vector Machine, HSSVM)對(duì)密封端面接觸狀態(tài)的識(shí)別方法。試驗(yàn)中以低轉(zhuǎn)速、非接觸摩擦狀態(tài)聲發(fā)射信號(hào)小波包能量特征訓(xùn)練超球面支持向量機(jī),能夠識(shí)別不同轉(zhuǎn)速下密封端面接觸狀態(tài)。(3)機(jī)械密封端面磨損程度不僅影響密封工作狀態(tài),而且決定密封泄漏量的大小。為了在沒(méi)有全歷程狀態(tài)數(shù)據(jù)的情況下對(duì)機(jī)械密封端面做出較為準(zhǔn)確地磨損狀態(tài)評(píng)估,提出了基于偏置因子隱馬爾可夫模型(Bias Factorial Hidden MarkovModel,BFHMM)的機(jī)械密封磨損狀態(tài)評(píng)估技術(shù)。傳統(tǒng)的基于完備先驗(yàn)知識(shí)的監(jiān)測(cè)模型建立非常困難,而且普適性較差,本文研究在僅具備機(jī)械密封端面最初和嚴(yán)重磨損兩種狀態(tài)下的先驗(yàn)知識(shí),即在沒(méi)有全歷程狀態(tài)數(shù)據(jù)的情況下對(duì)機(jī)械密封運(yùn)行狀態(tài)作出較為準(zhǔn)確地評(píng)估,從而避免機(jī)械密封過(guò)度磨損,保證密封的正常使用和設(shè)備的安全運(yùn)行。(4)對(duì)機(jī)械密封的使用剩余壽命的預(yù)測(cè)是評(píng)定一套機(jī)械密封性能的重要指標(biāo)�？紤]到灰色理論能有效預(yù)測(cè)信號(hào)的總體趨勢(shì),而粒子濾波卻對(duì)其局部變化更為敏感。本文將兩種方法相結(jié)合,提出灰色粒子濾波預(yù)測(cè)方法：首先利用粒子濾波對(duì)曲線拐點(diǎn)進(jìn)行跟蹤修正,然后利用灰色理論擬合預(yù)測(cè)密封摩擦副的總體壽命曲線。數(shù)據(jù)證明,該方法能對(duì)機(jī)械密封摩擦副的剩余壽命進(jìn)行有效預(yù)測(cè)。本論文研究?jī)?nèi)容主要完成了對(duì)機(jī)械密封端面開(kāi)啟轉(zhuǎn)速檢測(cè),建立了密封端面接觸狀態(tài)和磨損狀態(tài)的識(shí)別評(píng)估模型,實(shí)現(xiàn)了對(duì)端面接觸狀態(tài)監(jiān)測(cè)、端面磨損程度評(píng)估及摩擦副剩余壽命預(yù)測(cè),為以后工業(yè)現(xiàn)場(chǎng)機(jī)械密封狀態(tài)監(jiān)測(cè)實(shí)施提供了理論依據(jù)和技術(shù)支持。
[Abstract]:Mechanical seal (Mechanical Seal MS) is a reaction kettle, centrifugal pump, compressor and turbine components such as mechanical device, rotary device for preventing leakage, save energy and protect the environment. If the reaction kettle, centrifugal pump, compressor and turbine etc. as a dynamic system of the heart, so the mechanical seal is in the heart of the valve. The mechanical seal condition monitoring (Mechanical Seal Condition Monitoring, MSCM) is to control the abnormal information and signs of deterioration of sealing equipment failure before, so that the project staff take place or reduce the possibility of targeted measures to prevent failure, thereby reducing due to failure caused by downtime and all the losses caused by downtime, reduce maintenance costs and improve enterprise finally the effective utilization rate of the equipment. This paper deeply discusses the domestic and foreign machinery in sealed condition Based on the research status of monitoring, through multi sensor monitoring experiments were conducted to further study on end face mechanical seal, the main contents are as follows: (1) mechanical seal to a close contact to prevent fluid leakage; on the other hand, seal gap can not be too small, to prevent excessive contact face in order to protect the damage the seals. Compatible with mechanical seal of low friction and a small amount of leakage and balance, must first be on the seal face opening speed of equipment operation for testing. Due to its direct feedback is very good on the mechanical seal face contact state of the acoustic emission signals, and bilateral Laplace wavelet can be well extracted from acoustic emission pulse in the signal, proposed to the bilateral asymmetric Laplace wavelet correlation coefficient method of acoustic emission signal detection based on the mechanical seal face opening speed. (2) mechanical seal end face contact The state directly affects the sealing performance and service life, so it is necessary to monitor the mechanical seal friction state. Because the acoustic emission signals from the spindle speed effect is very small, is studied by using the hypersphere support vector machine based on acoustic emission signals (Hyper-Sphere Support Vector Machine, HSSVM) on the recognition method of seal face contact state. During the experiment, low speed, non contact friction state of AE signal characteristics of wavelet packet energy training hypersphere support vector machine, to seal the contact state recognition under different speed. (3) mechanical seal wear not only affect the sealing state, and seal leakage rate. In the absence of the whole process to state data under the condition of mechanical seal wear to make a more accurate assessment, the bias factor of hidden Markov model based on Bias (Fa Ctorial Hidden MarkovModel, BFHMM) of the mechanical seal wear condition assessment. The traditional monitoring model based on the complete prior knowledge is very difficult, and poor universality, in this paper, only with the mechanical seal and the initial state of the serious wear of two kinds of prior knowledge, the whole process of state data. The mechanical seal running state to make more accurate evaluation, so as to avoid excessive wear of the mechanical seal, to ensure the safe operation of normal use and equipment sealing. (4) the residual life prediction of mechanical seal is an important index to evaluate a set of mechanical sealing performance. Considering the grey theory can effectively predict the overall trend signal but, but the local particle filter is more sensitive to the change. This paper combines the two methods, the gray prediction method is proposed: firstly, particle filter particle filter on. Line tracking inflection point correction, and then use the grey theory prediction of overall life curve fitting the sealing friction pair. Data show that this method can effectively predict the residual life of mechanical seal friction pair. The main contents of this dissertation were completed on the mechanical seal face opening speed detection, establishes the identification evaluation model of the contact state and the seal face wear condition, the contact state monitoring of end face wear and friction degree evaluation of residual life prediction, provide a theoretical basis and technical support for future industrial field monitoring implementation of the mechanical seal.

【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TH136

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