本文選題：振動信號 + 小波分析��； 參考：《西安理工大學(xué)》2017年碩士論文

【摘要】：振動是機械設(shè)備運行當中的一種常見現(xiàn)象。通過對振動信號的提取可以分析機械設(shè)備的運行狀態(tài)。由于滾動軸承是機械設(shè)備的關(guān)鍵零件,它的好壞與設(shè)備的正常與否息息相關(guān),因此對滾動軸承的振動信號進行研究有重要的意義。包絡(luò)譜分析法是振動信號常用的分析方法,為了提高算法運行的速度,快速得到結(jié)果,可以通過FPGA來實現(xiàn)。為完成以上要求,本文設(shè)計了一個滾動軸承振動測試系統(tǒng)并且開展了以下工作:(1)研制振動信號采集的硬件模塊。根據(jù)振動信號的特點選取了振動加速度傳感器作為數(shù)據(jù)的拾取裝置,通過調(diào)理電路的設(shè)計對采集到的信號進行預(yù)處理。數(shù)模轉(zhuǎn)換電路將處理過后的信號送入控制芯片當中進行存儲和處理,經(jīng)過無線Wi-Fi傳輸?shù)浇K端設(shè)備當中。(2)振動信號特征的提取。首先對常用的振動信號的分析方法進行了闡述,詳細介紹了幅值域分析、傅里葉分析、小波分析、Hilbert包絡(luò)譜分析的理論。對比這幾種理論方法,選取了一種基于小波分解和Hilbert包絡(luò)譜的振動信號分析方法。利用小波理論對信號進行不同頻段的分解,提取出含有故障信息的頻段,用Hilbert包絡(luò)譜分析找出故障特征頻率,同時在FPGA上實現(xiàn)該分析方法。(3)在滾動軸承實驗平臺上,利用振動數(shù)據(jù)采集的硬件裝置,采集存在損傷的故障軸承,結(jié)合小波和Hilbert包絡(luò)譜對其進行分析,得到故障特征頻率,對比FPGA和MATLAB得到的結(jié)果。通過實驗,將FPGA和MATLAB所得到故障頻率與理論值進行對照,證明了該振動信號采集分析系統(tǒng)是可行的,能夠快速有效的提取振動信號的特征信息。
[Abstract]:Vibration is a common phenomenon in the operation of mechanical equipment. The operating state of mechanical equipment can be analyzed by extracting vibration signal. Because the rolling bearing is the key part of the mechanical equipment, its quality is closely related to the normal or not of the equipment, so it is of great significance to study the vibration signal of the rolling bearing. Envelope spectrum analysis is a common method for vibration signal analysis. In order to improve the speed of the algorithm and get the results quickly, it can be realized by FPGA. In order to fulfill the above requirements, a rolling bearing vibration testing system is designed and the following work is carried out: 1) the hardware module of vibration signal acquisition is developed. According to the characteristics of the vibration signal, the vibration acceleration sensor is selected as the data pickup device, and the collected signal is preprocessed by the design of the conditioning circuit. The digital-to-analog conversion circuit sends the processed signal into the control chip for storage and processing, and then transmits it to the terminal device via wireless Wi-Fi to extract the characteristic of the vibration signal. Firstly, the common methods of vibration signal analysis are described, and the theory of amplitude range analysis, Fourier analysis and Hilbert envelope spectrum analysis is introduced in detail. Compared with these methods, a vibration signal analysis method based on wavelet decomposition and Hilbert envelope spectrum is selected. The wavelet theory is used to decompose the signal in different frequency bands, and the frequency band containing fault information is extracted, and the fault characteristic frequency is found by Hilbert envelope analysis. At the same time, the analysis method is realized on FPGA. The method is implemented on the rolling bearing experimental platform. Using the hardware device of vibration data acquisition, the fault bearing with damage is collected. The fault characteristic frequency is obtained by combining wavelet and Hilbert envelope spectrum, and the results obtained by FPGA and MATLAB are compared. Through experiments, the fault frequency obtained by FPGA and MATLAB is compared with the theoretical value. It is proved that the vibration signal acquisition and analysis system is feasible and can extract the characteristic information of vibration signal quickly and effectively.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH133.33;TP212

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