發(fā)布時間：2018-05-04 08:10

  本文選題：面向 + 城軌　； 參考：《北京交通大學》2015年博士論文

【摘要】：城市軌道交通是我國城鎮(zhèn)化和城市現代化的全局性和支撐性的基礎設施,是城市綜合交通的骨干交通方式。截止2012年底,全國城市軌道交通規(guī)劃總里程超過14000公里,覆蓋53個大中城市；截止2013年底,全國累計批復36個城市的軌道交通建設總里程約6000公里；累計建成開通運營總里程已達2266公里。 如何保障城市軌道交通系統的運營安全,提升運營維護水平,降低全生命周期運營成本已成為我國城市軌道交通可持續(xù)健康發(fā)展的瓶頸問題,迫切需要研發(fā)適應我國國情和運營管理機制的包括城軌列車走行部軸承運行狀態(tài)在途檢測、故障診斷和預警技術在內的軌道交通安全保障技術與裝備體系。 本文以形成符合國情和自主知識產權的城軌列車走行部軸承運營狀態(tài)在途監(jiān)測及預警關鍵理論技術與相關系統為目標,形成了具有普適意義的如下理論方法和關鍵技術及裝備： 本文對城軌列車走行部軸承在途故障診斷展開以下研究： 1.深入研究了城軌列車走行部軸承結構、振動機理和故障形式及原因,提出了多因素(徑向游隙、轉速、載荷、波紋度等)綜合作用下的城軌列車走行部軸承靜、動力學模型。分析了不同因素對系統的影響,得出軸承內在結構以及外部原因與征兆表現之間的內在聯系和映射關系,再結合城軌列車特定運營環(huán)境,確定走行部軸承的監(jiān)測參數與監(jiān)測部位,為后續(xù)城軌列車軸承疲勞壽命評估和在途故障辨識提供理論和技術支撐。 2.基于獲取的實時動載荷數據,并在軸承疲勞壽命分析理論的基礎上,構建了時變工況下城軌列車走行部軸承的疲勞壽命評估模型。首先系統分析了不同參數(轉速、載荷、節(jié)徑、滾動體數目)對軸承疲勞壽命的影響,在此基礎上,結合軌道交通列車時變運營工況,建立了變工況下走行部軸承疲勞壽命模型,并利用廣州地鐵時變工況環(huán)境下的數據對模型進行了測試,驗證了模型的合理性和有效性。 3.從基于實時數據特征提取方面考慮,提出了面向城軌列車走行部軸承多智能算法融合的在途故障辨識方法。在研究小波分析、包絡分析、經驗模態(tài)分解、神經網絡、遺傳算法等信號處理方法基礎上,融合諧波小波良好的時頻局部化特性和包絡解調的優(yōu)點,設計了基于諧波小波包絡分析的城軌列車軸承故障辨識方法；基于小波包的時頻性和神經網絡的自學習、自適應性,構建了基于小波包神經網絡的城軌列車軸承故障辨識方法：結合經驗模態(tài)分解方法精細的時頻解析度、神經網絡的自學習、自適應性和遺傳算法的全局搜索能力,建立了基于時頻域多維特征參量和遺傳神經網絡的城軌列車走行部軸承在途故障辨識方法,并利用不同工況下的故障數據對算法辨識精度和實時性進行測試,診斷結果表明面向城軌列車走行部軸承多智能算法融合的在途故障辨識方法具有較高的辨識精度和較快的診斷效率,從而為在途故障診斷系統的研發(fā)奠定基礎。 4.基于城軌列車走行部軸承多智能算法融合故障辨識方法的研究成果,并結合廣州地鐵現有安全監(jiān)測裝備,設計了城軌列車走行部軸承在途故障診斷系統,并通過試驗臺數據驗證了該系統故障辨識的準確性和實時性。
[Abstract]:Urban rail transit is a global and supporting infrastructure for urbanization and urban modernization in China. It is the backbone of urban integrated transportation. By the end of 2012, the total mileage of urban rail transit planning in China was more than 14000 kilometers, covering 53 large and medium-sized cities. By the end of 2013, the whole country has approved the rail transit of 36 cities in China. The total mileage of construction is about 6000 km, and the total mileage of the total operation has reached 2266 km.
How to ensure the operation safety of urban rail transit system, improve the level of operation and maintenance and reduce the cost of life cycle has become the bottleneck of the sustainable and healthy development of urban rail transit in our country. It is urgent to develop the running state of the bearing of urban rail train, which is adapted to the national conditions and operation management mechanism of our country. The technology and equipment system of rail traffic safety, including fault diagnosis and early warning technology.
The aim of this paper is to form the key theory and technology and related system of the bearing operation of urban rail train, which is in line with the national conditions and independent intellectual property rights, and forms the following theoretical methods and key technology and equipment.
In this paper, the following research is carried out on the fault diagnosis of bearing on the way of urban rail train.
1. the bearing structure, the vibration mechanism and the fault form and the cause of the bearing of the rail train are studied in depth. The bearing static and dynamic models of the track train under the multiple factors (radial clearance, rotational speed, load and waviness) are put forward. The influence of different factors on the system is analyzed, and the internal structure and external reasons of the bearing are analyzed. The internal relation and mapping relation between the sign performance and the specific operating environment of the rail train will be combined to determine the monitoring parameters and monitoring parts of the bearing of the walking train, and provide the theoretical and technical support for the bearing fatigue life assessment and the fault identification of the following urban rail train bearings.
2. based on the real-time dynamic load data obtained, and on the basis of the theory of bearing fatigue life analysis, a fatigue life assessment model for the bearing of the rail train in time varying condition is constructed. First, the effects of different parameters (rotational speed, load, diameter and number of rolling body) on the fatigue life of the bearing are analyzed systematically, and on this basis, the track is combined with the track. The fatigue life model of the bearing is established under the variable operating conditions. The model is tested by the data of the time-varying working conditions of Guangzhou metro, which verifies the rationality and effectiveness of the model.
3. based on the feature extraction of real time data, a method of fault identification is proposed, which is based on the wavelet analysis, envelope analysis, empirical mode decomposition, neural network, genetic algorithm and other signal processing methods, which combines the good time frequency localization of the harmonic wavelets. As well as the advantages of envelope demodulation, a fault identification method for urban rail bearing based on the harmonic wavelet envelopment analysis is designed. Based on the time frequency of the wavelet packet and self-learning and self-adaptive of the neural network, a fault identification method for urban rail bearing based on the wavelet packet neural network is constructed, and the precise time frequency of the method is combined with the empirical mode decomposition method. Resolution, self-learning of neural network, self-adaptive and global searching ability of genetic algorithm, a fault identification method for bearing in the walk part of urban rail train based on multi-dimensional characteristic parameters of time frequency domain and genetic neural network is established. The identification accuracy and real-time performance of the algorithm are tested by using the fault data under different working conditions, and the diagnosis results are obtained. The results show that the fault identification method for the multi intelligent algorithm fusion for the bearing of urban rail trains has higher identification precision and faster diagnosis efficiency, thus laying the foundation for the research and development of the fault diagnosis system in the road.
4. based on the research results of the fault identification method of multi intelligent algorithm for bearing of urban rail train, combined with the existing safety monitoring equipment in Guangzhou metro, the fault diagnosis system of the bearing in the walk part of the rail train is designed, and the accuracy and real time of the fault identification of the system is verified by the data of the test bench.

【學位授予單位】：北京交通大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：U279

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本文編號：1842266