本文選題：故障診斷 + 特征提取��； 參考：《燕山大學(xué)》2015年博士論文

【摘要】：液壓泵、滾動(dòng)軸承和齒輪等旋轉(zhuǎn)機(jī)械零部件在工業(yè)領(lǐng)域起著重要的傳動(dòng)作用,它們廣泛地應(yīng)用于冶金設(shè)備、工程機(jī)械、精密機(jī)床、精密儀器、航空航天、汽車、船舶和石油化工等重要工業(yè)領(lǐng)域。這些旋轉(zhuǎn)機(jī)械零部件通常大都處于高溫、高壓和高速等惡劣的工作環(huán)境,這也就導(dǎo)致了它們的健康狀態(tài)劣化速度比較快,具有較高的故障率。本文針對(duì)旋轉(zhuǎn)機(jī)械零部件的故障診斷問(wèn)題,研究了基于數(shù)學(xué)形態(tài)學(xué)和局部均值分解的方法。數(shù)學(xué)形態(tài)學(xué)和局部均值分解都是基于信號(hào)形態(tài)特征進(jìn)行的分析,所以二者都具有高度自適應(yīng)性和數(shù)據(jù)驅(qū)動(dòng)性。本文主要進(jìn)行了以下幾個(gè)方面的研究工作:(1)針對(duì)扁平型結(jié)構(gòu)元素長(zhǎng)度選擇的經(jīng)驗(yàn)性和任意性問(wèn)題,提出一種基于形態(tài)差值算子和功率譜熵相結(jié)合來(lái)確定扁平型結(jié)構(gòu)元素的最優(yōu)濾波長(zhǎng)度的方法。采用不同扁平型結(jié)構(gòu)元素長(zhǎng)度的形態(tài)差值算子對(duì)信號(hào)進(jìn)行濾波處理,對(duì)濾波后的信號(hào)計(jì)算功率譜熵,信號(hào)功率譜熵的最小值所對(duì)應(yīng)的長(zhǎng)度即為扁平型結(jié)構(gòu)元素的最優(yōu)濾波長(zhǎng)度,并采用仿真信號(hào)和液壓泵實(shí)測(cè)故障信號(hào)對(duì)所提方法的有效性進(jìn)行驗(yàn)證。(2)利用一種基于形態(tài)差值算子和形態(tài)指數(shù)相結(jié)合的方法對(duì)以滑靴磨損故障為研究對(duì)象的液壓泵健康狀態(tài)評(píng)估的問(wèn)題進(jìn)行研究。采用形態(tài)差值算子對(duì)滑靴不同磨損程度的故障信號(hào)進(jìn)行濾波處理,提取各種磨損程度下故障信號(hào)的形態(tài)指數(shù),分析形態(tài)指數(shù)對(duì)滑靴磨損故障及其劣化程度的變化規(guī)律和敏感性,實(shí)現(xiàn)對(duì)滑靴磨損故障的診斷及其劣化程度的評(píng)估,并利用液壓泵實(shí)測(cè)故障信號(hào)對(duì)所提方法的有效性進(jìn)行驗(yàn)證。(3)利用一種基于形態(tài)差值算子和差分熵相結(jié)合的方法對(duì)滾動(dòng)軸承早期輕度內(nèi)、外圈故障的診斷問(wèn)題進(jìn)行研究。采用形態(tài)差值算子對(duì)故障信號(hào)進(jìn)行濾波處理,差分熵提取濾波后信號(hào)在時(shí)域中的沖擊,根據(jù)沖擊突變點(diǎn)的時(shí)間間隔和特定故障信號(hào)在時(shí)域中的周期性沖擊間隔相一致的思想來(lái)實(shí)現(xiàn)對(duì)滾動(dòng)軸承早期輕度內(nèi)、外圈故障的有效診斷,并利用仿真信號(hào)和滾動(dòng)軸承實(shí)測(cè)故障信號(hào)對(duì)所提方法的有效性進(jìn)行驗(yàn)證。(4)針對(duì)乘積分量的解調(diào)和單尺度形態(tài)學(xué)分析的結(jié)構(gòu)元素長(zhǎng)度選擇的經(jīng)驗(yàn)性和主觀性問(wèn)題,提出一種基于局部均值分解和改進(jìn)自適應(yīng)多尺度形態(tài)學(xué)分析相結(jié)合的方法。采用局部均值分解方法對(duì)信號(hào)進(jìn)行分解,篩選若干個(gè)含有特征信息最豐富的乘積分量作為解調(diào)用數(shù)據(jù)源,基于扁平型、三角型和半圓型結(jié)構(gòu)元素的改進(jìn)自適應(yīng)多尺度形態(tài)學(xué)分析方法對(duì)其進(jìn)行解調(diào)分析,得到有效解調(diào)閾值區(qū)間(即在此區(qū)間,改進(jìn)自適應(yīng)多尺度形態(tài)學(xué)分析的解調(diào)效果要優(yōu)于改進(jìn)前自適應(yīng)多尺度形態(tài)學(xué)分析)和最優(yōu)解調(diào)閾值點(diǎn)。此外,將最優(yōu)解調(diào)結(jié)果和改進(jìn)前自適應(yīng)多尺度形態(tài)學(xué)分析、Hilbert變換、Teager Kaiser能量算子和局部均值分解的解調(diào)結(jié)果進(jìn)行對(duì)比,并利用液壓泵實(shí)測(cè)故障信號(hào)對(duì)所提方法的有效性進(jìn)行驗(yàn)證。(5)針對(duì)齒輪故障的診斷問(wèn)題,提出一種基于局部均值分解和廣義形態(tài)分形維數(shù)相結(jié)合的方法。采用局部均值分解方法對(duì)信號(hào)進(jìn)行分解,篩選若干個(gè)含有最豐富特征信息的乘積分量作為數(shù)據(jù)源進(jìn)行廣義形態(tài)分形維數(shù)的提取,選取某些能夠有效地表征齒輪運(yùn)行狀態(tài)非線性信息的維數(shù)作為特征向量,利用核模糊C均值聚類方法進(jìn)行故障診斷。此外,還對(duì)信號(hào)長(zhǎng)度、轉(zhuǎn)速和負(fù)載扭矩對(duì)廣義形態(tài)分形維數(shù)的影響進(jìn)行分析。并利用仿真信號(hào)和齒輪實(shí)測(cè)故障信號(hào)對(duì)所提方法的有效性進(jìn)行驗(yàn)證。(6)利用基于峭度、能量和均方差的選擇方法對(duì)合理地選取含有特征信息豐富的乘積分量作為數(shù)據(jù)源的問(wèn)題進(jìn)行研究。采用局部均值分解方法對(duì)原信號(hào)進(jìn)行分解,分別提取原信號(hào)和各個(gè)乘積分量的峭度、能量和均方差,并分別將這三個(gè)指標(biāo)組成一個(gè)指標(biāo)向量,計(jì)算原信號(hào)和各個(gè)乘積分量的指標(biāo)向量之間的歐氏距離,選取若干個(gè)最小歐氏距離值所對(duì)應(yīng)的乘積分量作為數(shù)據(jù)源,并利用液壓泵實(shí)測(cè)故障信號(hào)驗(yàn)證所提方法的有效性。
[Abstract]:Rotating machinery parts, such as hydraulic pumps, rolling bearings and gears, play an important transmission role in industrial fields. They are widely used in metallurgical equipment, engineering machinery, precision machine tools, precision instruments, aerospace, automobile, ship and petrochemical industry. These parts are usually in high temperature, high pressure and high pressure. High speed and other bad working conditions have resulted in the rapid deterioration of their health state and high failure rate. In this paper, a method based on mathematical morphology and local mean decomposition is studied for the fault diagnosis of rotating machinery parts. The mathematical morphology and local mean mean decomposition are based on the characteristics of signal morphology. The analysis is carried out, so the two are highly adaptive and data driven. This paper mainly conducts the following research work: (1) aiming at the empiricism and arbitrariness of the length selection of the flat structure element, a combination of the morphological difference operator and the power spectral entropy is proposed to determine the most flat structural elements. The method of optimal filtering length is used to filter the signal with the morphological difference operator of the length of different flat structure elements. The power spectral entropy of the filtered signal is calculated. The length of the minimum value of the signal power spectrum entropy is the optimal filter length of the flat structure element, and the simulation signal and the hydraulic pump are used to measure the fault letter. The validity of the proposed method is verified. (2) a method based on the combination of morphological difference operator and morphological index is used to study the problem of the health state evaluation of the hydraulic pump with the slipper wear fault as the research object. The morphological difference operator is used to filter the fault signals of the slipper with different wear degrees. The morphological index of the fault signal under various degrees of wear is analyzed, and the change law and sensitivity of the slipper wear fault and its deterioration degree are analyzed by the morphological index. The diagnosis and deterioration degree of the slipper wear fault are evaluated, and the effectiveness of the proposed method is verified by using the measured fault signal of the hydraulic pump. (3) using a kind of shape based on the shape of the fault signal. The method of state difference operator and differential entropy is used to study the diagnosis of the early mild inner and outer fault of rolling bearing. The morphological difference operator is used to filter the fault signal, the differential entropy is used to extract the impact of the signal in the time domain, and the time interval of the shock point and the specific fault signal in the time domain. The idea of periodic impact interval is consistent to realize the effective diagnosis of early mild inner and outer fault of rolling bearing, and verify the validity of the proposed method using the simulation signal and the measured fault signal of the rolling bearing. (4) the empiricism of the structural element length selection for the demodulation of the product component and the single scale morphologic analysis. A method based on local mean decomposition and improved adaptive multi-scale morphological analysis is proposed. The local mean decomposition method is used to decompose the signal, and several product components with the most abundant feature information are selected as the demodulation data source, based on the flat, triangular and semicircular structure elements. An improved adaptive multiscale morphological analysis method is used to demodulate and analyze it, and the effective demodulation threshold interval is obtained (i.e., the demodulation effect of the improved adaptive multi-scale morphological analysis is better than the improved adaptive multiscale morphological analysis) and the optimal demodulation threshold point. Multiscale morphological analysis, Hilbert transformation, Teager Kaiser energy operator and local mean decomposition are compared, and the effectiveness of the proposed method is verified by using the measured fault signal of the hydraulic pump. (5) in view of the diagnosis of gear fault, a kind of local mean decomposition and generalized fractal dimension fractal dimension are proposed. The local mean decomposition method is used to decompose the signal and select the product components with the most abundant feature information as the data source to extract the generalized fractal dimension, and select some dimensions of the nonlinear information of the gear running state effectively as the feature vectors, and use the kernel fuzzy C mean clustering. In addition, the effect of the signal length, speed and load torque on the generalized fractal dimension is analyzed. The validity of the proposed method is verified by the simulation signal and the measured fault signal of the gear. (6) the selection method based on kurtosis, energy and mean square deviation is used to select the characteristic letter. The partial mean decomposition method is used to decompose the original signal and extract the kurtosis, energy and mean square of the original signal and the product components respectively, and the three indexes are composed of an index vector to calculate the original signal and the index vector of the product components respectively. Euclidean distance is used to select the product components corresponding to a number of minimum Euclidean distance values as the data source, and the effectiveness of the proposed method is verified by a hydraulic pump fault signal measured by a hydraulic pump.

【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：TH17

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2 吳家j;基于數(shù)學(xué)形態(tài)學(xué)和局部預(yù)測(cè)的短期風(fēng)能預(yù)測(cè)研究[D];華南理工大學(xué);2015年

3 郭莉亞;基于數(shù)學(xué)形態(tài)學(xué)的牽引供電系統(tǒng)電能質(zhì)量分析[D];西南交通大學(xué);2015年

4 鄧文豪;基于數(shù)學(xué)形態(tài)學(xué)的高速列車安全性態(tài)分析[D];西南交通大學(xué);2015年

5 劉坤;數(shù)學(xué)形態(tài)學(xué)在牽引供電繼電保護(hù)中的應(yīng)用[D];西南交通大學(xué);2015年

6 王春霞;基于數(shù)學(xué)形態(tài)學(xué)的遙感影像人工草地提取研究[D];內(nèi)蒙古工業(yè)大學(xué);2015年

7 馬玉曉;基于數(shù)學(xué)形態(tài)學(xué)—小波分析組合算法的牽引網(wǎng)故障判定方法[D];東華理工大學(xué);2015年

8 李凱;基于數(shù)學(xué)形態(tài)學(xué)的故障暫態(tài)信號(hào)研究[D];河南理工大學(xué);2014年

9 王宇青;灰度膨脹(腐蝕)方程求解及相關(guān)問(wèn)題[D];蘇州科技學(xué)院;2015年

10 宋彥坤;基于數(shù)學(xué)形態(tài)學(xué)的電力電纜行波故障測(cè)距研究[D];河北科技大學(xué);2015年

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