本文選題：齒輪箱 + EMD��； 參考：《華北水利水電大學(xué)》2017年碩士論文

【摘要】：齒輪箱具有結(jié)構(gòu)緊湊,承載能力強(qiáng),傳動效率高,可靠性強(qiáng)等優(yōu)點,能夠滿足高速大功率及低速大扭矩的傳動要求,是各種機(jī)械動力傳動系統(tǒng)的重要裝置,其工作狀態(tài)是否正常對運動和動力的傳輸具有重要影響,一旦發(fā)生事故,將會造成嚴(yán)重影響,因此基于EMD和FastICA算法對齒輪箱故障診斷進(jìn)行研究具有重要的理論價值和現(xiàn)實意義。本文的主要研究內(nèi)容是基于EMD和FastICA算法的單通道盲源分離方法在齒輪箱故障診斷的應(yīng)用。在理論方面,主要分析了齒輪的振動機(jī)理和滾動軸承的振動機(jī)理,研究了齒輪箱中齒輪、軸承、軸和箱體的若干個典型故障,包括斷齒、齒面磨損、齒輪誤差、齒輪偏心、外圈故障、內(nèi)圈故障、保持架故障、滾動體故障、軸不對中、軸不平衡、箱體共振,建立了對齒輪箱故障的整體認(rèn)識,為后期進(jìn)行齒輪箱的故障診斷奠定理論基礎(chǔ)。在實驗方面,在齒輪箱動力模擬系統(tǒng)設(shè)備的基礎(chǔ)上,人為設(shè)置齒輪箱各種不同工況(齒輪箱正常、齒輪齒面磨損故障、缺齒故障和復(fù)合故障),通過壓電式加速度傳感器和激光轉(zhuǎn)速傳感器將齒輪箱的振動信號傳遞到計算機(jī)上的HG8916綜合數(shù)據(jù)采集故障診斷系統(tǒng),利用HG8916的數(shù)據(jù)采集模塊中的時域數(shù)據(jù)采集模塊采集信號,并觀察信號的時域特征,然后將HG8916采集出的信號導(dǎo)出,轉(zhuǎn)換為txt格式。針對單一通道信號,在MATLAB中編寫程序,調(diào)用EMD程序?qū)⑿盘栠M(jìn)行分解成IMF分量,根據(jù)改進(jìn)的奇異值分解法進(jìn)行源數(shù)估計,重組虛擬信號,再調(diào)用FastICA算法對信號進(jìn)行處理,提取盲源分離矩陣的奇異值作為信號故障特征,通過BP神經(jīng)網(wǎng)絡(luò)進(jìn)行分類識別和判斷,得出故障診斷的結(jié)果。實驗取得了良好的效果。通過實驗驗證可以得出以下結(jié)論:基于EMD和Fast ICA算法的單通道盲源分離方法綜合了EMD算法和FastICA算法的優(yōu)點,原理和計算相對簡單,且操作方便,不存在人為主觀因素,非常適合齒輪箱故障診斷的應(yīng)用。
[Abstract]:The gearbox has the advantages of compact structure, strong bearing capacity, high transmission efficiency and high reliability. It can meet the requirements of high speed, high power and low speed and large torque, and is an important device of various mechanical power transmission systems.Whether its working state is normal or not has an important influence on the transmission of motion and power. Once an accident occurs, it will cause serious impact. Therefore, the research of gearbox fault diagnosis based on EMD and FastICA algorithm has important theoretical value and practical significance.The main research content of this paper is the application of single channel blind source separation method based on EMD and FastICA algorithm in gearbox fault diagnosis.In theory, the vibration mechanism of gear and the vibration mechanism of rolling bearing are analyzed, and some typical faults of gear, bearing, shaft and box in gear box are studied, including tooth breaking, tooth surface wear, gear error, gear eccentricity.Outer ring fault, inner ring fault, cage fault, rolling body fault, shaft misalignment, shaft imbalance, box resonance, established the overall understanding of the gearbox fault, and laid a theoretical foundation for the fault diagnosis of the gearbox in the later stage.In the aspect of experiment, on the basis of the gear box dynamic simulation system equipment, the gear box is artificially set up various different working conditions (gear box normal, gear tooth surface wear failure,The vibration signal of gearbox is transmitted to the HG8916 integrated data acquisition fault diagnosis system by piezoelectric accelerometer and laser speed sensor.The time-domain data acquisition module of HG8916 is used to collect signals and observe the time-domain characteristics of the signals. Then the signals collected by HG8916 are exported and converted into txt format.For single channel signal, program is written in MATLAB, EMD program is called to decompose the signal into IMF component, the source number is estimated according to the improved singular value decomposition method, the virtual signal is reorganized, and then the FastICA algorithm is called to process the signal.The singular value of the blind source separation matrix is extracted as the signal fault feature, and the fault diagnosis results are obtained by BP neural network.The experiment has achieved good results.The experimental results show that the single channel blind source separation method based on EMD and Fast ICA algorithm combines the advantages of EMD algorithm and FastICA algorithm. The principle and calculation are relatively simple, the operation is convenient, and there are no artificial subjective factors.It is very suitable for gearbox fault diagnosis.
【學(xué)位授予單位】：華北水利水電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH132.41

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