本文選題：人工免疫　切入點：證據(jù)理論　出處：《太原理工大學(xué)》2011年碩士論文　論文類型：學(xué)位論文

【摘要】：旋轉(zhuǎn)機械廣泛應(yīng)用于工業(yè)領(lǐng)域,其主要由轉(zhuǎn)子、支撐轉(zhuǎn)子的軸承系統(tǒng)、定子或機器殼體、聯(lián)軸器等部件構(gòu)成,通過旋轉(zhuǎn)運動來完成工作。旋轉(zhuǎn)機械作為一些工業(yè)部門的關(guān)鍵核心設(shè)備,企業(yè)的生產(chǎn)將直接受到這些設(shè)備運行狀況優(yōu)劣的影響,如果發(fā)生故障停機,將帶來巨大的經(jīng)濟(jì)損失和嚴(yán)重的甚至災(zāi)難性的后果。故障診斷技術(shù),即了解機械的運行狀態(tài),預(yù)測其可靠性,識別機械故障的部位、原因、危險程度等,并預(yù)報其發(fā)展趨勢,最后針對診斷情況指導(dǎo)實施維護(hù)的技術(shù),其目的是為了減少故障發(fā)生帶來的損失。隨著科技的發(fā)展,機械設(shè)備的復(fù)雜程度越來越高,并發(fā)故障已成為故障診斷的常見問題,而且并發(fā)故障具有的復(fù)雜性、層次性、相關(guān)性、不確定性等特點,給正確診斷并發(fā)故障帶來了很大困難。本文即針對這一問題,將人工免疫與證據(jù)理論集成,構(gòu)建了并發(fā)故障診斷模型,通過實驗驗證,該模型可以有效的實現(xiàn)對并發(fā)故障的診斷。 受生物免疫系統(tǒng)的啟發(fā)發(fā)展而來的人工免疫系統(tǒng),為故障診斷帶來了新的思路。其中由生物免疫系統(tǒng)“自己”-“非己”識別機理衍生得到的陰性選擇算法,使得人工免疫系統(tǒng)應(yīng)用于故障診斷中可以有效的識別機械設(shè)備的工作狀態(tài)。結(jié)合無量綱指標(biāo)不受載荷、工況、轉(zhuǎn)速等工作條件影響的優(yōu)勢,構(gòu)建多無量綱免疫檢測器,利用這些無量綱免疫檢測器可以使從傳感器獲取的機械設(shè)備的振動信號分析處理為各無量綱指標(biāo)范圍,作為各種故障的特征信息進(jìn)行后續(xù)的分析判斷。證據(jù)理論在量測和組合、不確定性的表示方面的優(yōu)勢使得許多學(xué)者將它引入并發(fā)故障診斷中來。用證據(jù)理論對人工免疫系統(tǒng)的無量綱免疫檢測器得到的故障特征信息進(jìn)行融合來實現(xiàn)對故障的最終判定,這就是本文提出的人工免疫與證據(jù)理論集成應(yīng)用于旋轉(zhuǎn)機械故障診斷的思路。 本文在實驗過程中應(yīng)用了優(yōu)化的無量綱指標(biāo),這些新的無量綱指標(biāo)是利用遺傳算法優(yōu)化得到的,較好的解決了原有無量綱指標(biāo)只對部分故障敏感的缺陷。并對證據(jù)理論進(jìn)行了擴展,充分考慮了不同指標(biāo)對不同故障的診斷能力、敏感程度不同的特性,采用加權(quán)證據(jù)理論的方式對故障特征信息進(jìn)行融合,從而提高了診斷的可靠性和靈敏度。實驗驗證,人工免疫和證據(jù)理論集成的方法對于旋轉(zhuǎn)機械并發(fā)故障的診斷切實可行。
[Abstract]:Rotating machinery is widely used in industry, which is mainly composed of a rotor bearing system supported rotor, stator or machine casing, couplings and other components, through rotation of rotating machinery to complete the work. As the key equipment in some industries, the production of the enterprise will have a direct impact on the health of the equipment operation, if a fault occurs stop, will bring huge economic losses and even disastrous consequences. The fault diagnosis technology, to understand the mechanical running condition, forecast the reliability, identify causes of mechanical failure of the parts, degree of risk, and forecast its development trend, according to the diagnosis of the situation to guide the implementation of maintenance technology, its purpose is to to reduce the loss caused by the fault. With the development of science and technology, mechanical equipment becomes more and more complex, concurrent fault has become a common problem of fault diagnosis, But with the complexity of concurrent fault hierarchy, correlation, uncertainty, brought great difficulties to the correct diagnosis of concurrent fault. This article is aimed at this problem, the integration of artificial immunity and evidence theory, constructs the concurrent fault diagnosis model, through experimental verification, the model can be the diagnosis of concurrent fault effectively.
Artificial immune system inspired by the biological immune system development, brings a new approach for fault diagnosis. The biological immune system "-" non self recognition mechanism derived from negative selection algorithm, the application of artificial immune system in fault diagnosis of mechanical equipment to identify effective working condition with dimensionless index is not affected by the load conditions, the working conditions of the influence of the speed advantage, build multi dimensionless immune detectors, using these dimensionless immune detectors can make the vibration signals of mechanical equipment obtained from the sensor analysis for the dimensionless index range, as the characteristic information of fault analysis and judgment in the future. Evidence theory test and combination in the amount of uncertainty is expressed in terms of advantage makes many scholars put it into the concurrent fault diagnosis. The use of evidence theory The fault feature information obtained from the non dimensional immune detector of immune system is fused to achieve the final judgement of faults. This is the idea of artificial immune and evidence theory integrated in rotating machinery fault diagnosis.
The dimensionless index in this paper are applied in the optimization, the new dimensionless index is obtained by using genetic algorithm optimization, to solve the defects of original dimensionless index only part of the fault sensitive. And the evidence theory is extended, considering the different indicators of the different fault diagnosis ability. The characteristics of different sensitive degree, using the weighted evidence theory to fault information fusion, so as to improve the reliability of diagnosis and sensitivity. Experimental verification, artificial immune system and evidence theory integrated method for rotary machinery fault diagnosis to concurrency is feasible.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號】：TH165.3;TP18

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