本文選題：故障特征提取 + BP神經(jīng)網(wǎng)絡(luò)�。� 參考：《浙江大學(xué)》2015年碩士論文

【摘要】：浙江大學(xué)化工機(jī)械研究所高速旋轉(zhuǎn)機(jī)械實(shí)驗(yàn)受南通某公司委托開發(fā)一套旋轉(zhuǎn)機(jī)械故障診斷和現(xiàn)場動(dòng)平衡系統(tǒng),用于監(jiān)測大中型風(fēng)機(jī)轉(zhuǎn)子的運(yùn)行狀態(tài),提前預(yù)測與判定設(shè)備故障類型,避免故障帶來的嚴(yán)重?fù)p失,確保設(shè)備安全可靠運(yùn)行；并對(duì)不平衡轉(zhuǎn)子進(jìn)行現(xiàn)場動(dòng)平衡以減小振動(dòng)。本文的主要研究工作如下：(1)研究了振動(dòng)信號(hào)故障特征提取與故障模式識(shí)別的方法。針對(duì)小波包能量特征參數(shù)不具有時(shí)間特性和自適應(yīng)性的局限性,引入小波包能量距作為特征參數(shù),給出了根據(jù)轉(zhuǎn)子轉(zhuǎn)速調(diào)整采樣頻率的關(guān)系式,從而使提取的故障特征不僅具有時(shí)頻特性,而且對(duì)不同轉(zhuǎn)速下的同種故障具有自適應(yīng)性,并利用仿真信號(hào)和不同轉(zhuǎn)速的不平衡故障數(shù)據(jù)進(jìn)行了驗(yàn)證,驗(yàn)證結(jié)果表明,該方法簡化了小波包選擇過程,很好的統(tǒng)一了不同轉(zhuǎn)速故障信號(hào)的特征參數(shù)。實(shí)驗(yàn)?zāi)M突加不平衡、不平衡、不對(duì)中、碰磨等故障,對(duì)振動(dòng)數(shù)據(jù)進(jìn)行時(shí)域、頻域和小波包分析,提取不同故障的能量距特征參數(shù),用于訓(xùn)練和測試BP神經(jīng)網(wǎng)絡(luò),結(jié)果表明本文設(shè)計(jì)的BP神經(jīng)網(wǎng)絡(luò)具有較高的識(shí)別率。(2)研究了剛性轉(zhuǎn)子現(xiàn)場動(dòng)平衡方法,建立了不平衡振動(dòng)的軸心軌跡和振動(dòng)高點(diǎn)的計(jì)算模型,將振動(dòng)高點(diǎn)影響系數(shù)法應(yīng)用到現(xiàn)場動(dòng)平衡中,解決了傳統(tǒng)動(dòng)平衡方法尋找振動(dòng)高點(diǎn)的難題,單次動(dòng)平衡減振率明顯提高,大大縮短了現(xiàn)場動(dòng)平衡時(shí)間。(3)研發(fā)了一套旋轉(zhuǎn)機(jī)械故障診斷與現(xiàn)場動(dòng)平衡系統(tǒng)。采用工控機(jī)+PLC+采集卡+傳感器組+儀表組搭建系統(tǒng)硬件,并編寫了相應(yīng)的故障診斷與現(xiàn)場動(dòng)平衡軟件,實(shí)現(xiàn)旋轉(zhuǎn)機(jī)械的狀態(tài)監(jiān)測、故障診斷與現(xiàn)場動(dòng)平衡等功能。轉(zhuǎn)子試驗(yàn)臺(tái)模擬測試和現(xiàn)場風(fēng)機(jī)轉(zhuǎn)子測試結(jié)果表明,本文研發(fā)的系統(tǒng)可靠性高、滿足設(shè)計(jì)要求、動(dòng)平衡效率高達(dá)90%以上。
[Abstract]:The high-speed rotating machinery experiment of the Institute of Chemical Machinery of Zhejiang University was commissioned by a company in Nantong to develop a rotating machinery fault diagnosis and on-site dynamic balancing system for monitoring the running status of large and medium-sized fan rotors. In order to avoid the serious loss caused by the fault and ensure the safe and reliable operation of the equipment, the dynamic balancing of the unbalanced rotor is carried out in the field to reduce the vibration. The main work of this paper is as follows: 1) the methods of fault feature extraction and fault pattern recognition for vibration signal are studied. In view of the limitation of wavelet packet energy characteristic parameter which has no time characteristic and adaptability, the wavelet packet energy distance is introduced as the characteristic parameter, and the relation of adjusting sampling frequency according to rotor speed is given. Thus, the extracted fault features not only have time-frequency characteristics, but also have self-adaptability to the same fault at different rotational speeds. The simulation signals and unbalanced fault data of different rotational speeds are used to verify the proposed method. This method simplifies the selection process of wavelet packet and unifies the characteristic parameters of different speed fault signals. The experiment simulates the faults such as sudden unbalance, misalignment and rubbing. The vibration data are analyzed in time domain, frequency domain and wavelet packet, and the characteristic parameters of energy distance of different faults are extracted for training and testing BP neural network. The results show that the BP neural network designed in this paper has a high recognition rate. The field dynamic balancing method of rigid rotor is studied, and the calculation model of the axis track and vibration height of the unbalanced vibration is established. The influence coefficient method of vibration high point is applied to the field dynamic balance, which solves the problem of finding the vibration high point by the traditional dynamic balance method, and the damping rate of the single dynamic balance is obviously increased. A rotating machinery fault diagnosis and field dynamic balancing system is developed. The hardware of the system is set up by using PLC data acquisition card of industrial control computer, and the corresponding software of fault diagnosis and field dynamic balance is compiled to realize the functions of condition monitoring, fault diagnosis and field dynamic balance of rotating machinery. The results of rotor test and field fan rotor test show that the system developed in this paper has high reliability and meets the design requirements, and the dynamic balance efficiency is over 90%.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TQ050.7;TP183

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 楊建剛,謝東建,高N，

本文編號(hào)：1820645