本文選題：不精確概率 + 證據(jù)理論��； 參考：《中國科學(xué)技術(shù)大學(xué)》2017年碩士論文

【摘要】：現(xiàn)代化工業(yè)的蓬勃發(fā)展,使得生產(chǎn)生活與各類機(jī)械設(shè)備密不可分。隨著機(jī)械設(shè)備的大型化、自動化程度越來越高,一旦其發(fā)生故障就容易造成嚴(yán)重的危害,因此,對機(jī)械設(shè)備故障診斷的研究具有重要意義。本文調(diào)研了現(xiàn)有的故障診斷方法,其中,多源傳感器信息融合的方法由于可以利用多源信息更為全面地反映系統(tǒng)的工作狀態(tài)而受到廣泛應(yīng)用。故障發(fā)生時系統(tǒng)采集的數(shù)據(jù)并非是固定不變的,而是包含有大量的不確定性,為了對這些包含著不確定因素的多源信息處理而得到可靠的診斷結(jié)果,常用DS證據(jù)理論作為理論基礎(chǔ)進(jìn)行不確定性推理。本文通過對通用證據(jù)理論故障診斷框架的分析,發(fā)現(xiàn)該診斷框架在證據(jù)生成以及決策診斷方面尚存在不足之處。同樣作為不確定性推理方法,不精確概率理論相對而言是一個更為一般化的模型,對不確定信息的表征更符合實(shí)際需求,在處理數(shù)據(jù)的過程中更符合人的思維習(xí)慣,其多種決策準(zhǔn)則也適用于不同精度要求的系統(tǒng)�；诖�,本文提出了基于不精確概率的故障診斷方法,并以隔振平臺為實(shí)驗(yàn)對象驗(yàn)證了方法的可行性。首先,構(gòu)建了不精確概率理論下的故障診斷框架。本文第三章通過對傳統(tǒng)證據(jù)生成方法的改進(jìn)得到了下概率的生成方法,設(shè)計了可以表示專家決策傾向的診斷價值函數(shù),將故障診斷問題轉(zhuǎn)化為在現(xiàn)有條件下對價值函數(shù)期望值的比較與決策問題。隨后比較了特征級融合和決策級融合在本方法中的相同與不同之處,采取特征級融合對數(shù)據(jù)進(jìn)行融合。最后,通過實(shí)例分析了不同決策準(zhǔn)則的特點(diǎn)。本文第四章以隔振平臺為研究對象,構(gòu)造了多類故障,使用推進(jìn)式窗口對數(shù)據(jù)采樣,以三路傳感器采樣數(shù)據(jù)為原始數(shù)據(jù),對不同特征參數(shù)進(jìn)行了大量的分析和對比以選定特征參數(shù),實(shí)現(xiàn)了對隔振平臺故障類型的判斷。第五章首先以第四章為基礎(chǔ),針對振動發(fā)散類故障對診斷時間要求比較高的問題,采用本文方法實(shí)現(xiàn)了對故障時間的診斷。針對特征參數(shù)質(zhì)量較差時,使用不精確概率診斷時會出現(xiàn)誤判的情況,設(shè)計了結(jié)合使用DS證據(jù)理論與不精確概率理論的方法,在保證診斷時間的情況下有效減少了誤判。實(shí)驗(yàn)結(jié)果表明,本文提出的方法用于故障診斷是可行有效的。
[Abstract]:With the vigorous development of modern industry, production and life are closely related to all kinds of machinery and equipment. With the large scale of machinery and equipment, the degree of automation is becoming higher and higher. Once it breaks down, it is easy to cause serious harm. Therefore, it is of great significance to study the fault diagnosis of machinery and equipment. In this paper, the existing fault diagnosis methods are investigated. Among them, the multi-source sensor information fusion method is widely used because it can reflect the working state of the system more comprehensively by using the multi-source information. When the fault occurs, the data collected by the system is not fixed, but contains a lot of uncertainties. In order to process the multi-source information with uncertain factors, the reliable diagnosis results can be obtained. DS evidence theory is often used as the theoretical basis for uncertainty reasoning. Based on the analysis of the general evidence theory fault diagnosis framework, it is found that there are still shortcomings in the evidence generation and decision diagnosis. As an uncertain reasoning method, the theory of inexact probability is a more general model, and the representation of uncertain information is more in line with the actual needs, and is more in line with the thinking habits of people in the process of processing data. Many of its decision criteria are also applicable to systems with different precision requirements. Based on this, a fault diagnosis method based on imprecise probability is proposed, and the feasibility of the method is verified by taking the vibration isolation platform as the experimental object. Firstly, a fault diagnosis framework based on imprecise probability theory is constructed. In the third chapter, the method of generating the lower probability is obtained by improving the traditional method of evidence generation, and the diagnostic value function which can express the tendency of expert decision is designed. The problem of fault diagnosis is transformed into the problem of comparison and decision of the expected value of value function under existing conditions. Then, the similarity and difference of feature level fusion and decision level fusion in this method are compared, and the feature level fusion is adopted to fuse the data. Finally, the characteristics of different decision criteria are analyzed by examples. In the fourth chapter, the vibration isolation platform is taken as the research object, and many kinds of faults are constructed. The data are sampled by propulsive window, and the original data are sampled by three sensors. The different characteristic parameters are analyzed and compared in order to select the characteristic parameters, and the fault types of vibration isolation platform can be judged. In the fifth chapter, based on the fourth chapter, aiming at the problem that the diagnosis time of vibration divergence type faults is high, the fault time diagnosis is realized by the method of this paper. In order to solve the problem that inaccurate probability diagnosis will occur when the quality of feature parameters is poor, a method combining DS evidence theory and imprecise probability theory is designed, which can effectively reduce the misjudgment under the condition of ensuring the diagnosis time. The experimental results show that the proposed method is feasible and effective in fault diagnosis.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH17

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