【摘要】：大型機械設(shè)備組成結(jié)構(gòu)復雜,容易產(chǎn)生故障,通過對大型機械設(shè)備的振動系統(tǒng)故障診斷,提高大型機械設(shè)備的穩(wěn)定運行性能。傳統(tǒng)的故障診斷方法采用海量振動樣本特征數(shù)據(jù)聚類分析方法進行故障分類和診斷,診斷性能受到振動數(shù)據(jù)樣本采集和環(huán)境的特征的限制,故障檢測效果不好。提出一種基于大型機械設(shè)備振動系統(tǒng)故障特征專家系統(tǒng)構(gòu)建的故障診斷模型,并采用abaqus軟件進行仿真分析。構(gòu)建故障診斷專家系統(tǒng),包括對模糊數(shù)據(jù)庫、模糊知識庫和模糊推理機的構(gòu)建,設(shè)計故障診斷的神經(jīng)網(wǎng)絡(luò)模糊控制學習算法,通過設(shè)計人機結(jié)構(gòu),實現(xiàn)對大型機械設(shè)備振動系統(tǒng)故障的準確推斷決策。利用abaqus軟件在計算機上建立測試虛擬樣機,實現(xiàn)故障診斷在線模型仿真,了解復雜機械系統(tǒng)設(shè)計的故障運行性能。仿真結(jié)果表明,該系統(tǒng)能有效提高對大型機械設(shè)備振動系統(tǒng)的故障診斷能力,實現(xiàn)智能故障診斷控制和自適應故障處理,在機械狀態(tài)監(jiān)測等領(lǐng)域具有較好的應用價值。
[Abstract]:The composition and structure of large mechanical equipment is complex and easy to cause faults. Through the fault diagnosis of vibration system of large mechanical equipment, the stable operation performance of large mechanical equipment can be improved. The traditional fault diagnosis method uses massive vibration sample feature data clustering analysis method for fault classification and diagnosis. The diagnosis performance is limited by vibration data collection and environmental characteristics, and the fault detection effect is not good. A fault diagnosis model based on fault characteristics expert system of vibration system of large mechanical equipment is proposed, and the simulation analysis is carried out by using abaqus software. The fault diagnosis expert system is constructed, including the construction of fuzzy database, fuzzy knowledge base and fuzzy inference engine, the learning algorithm of neural network fuzzy control for fault diagnosis is designed, and the man-machine structure is designed. The accurate inference and decision of vibration system fault of large mechanical equipment is realized. The virtual prototype of test is established on the computer by using abaqus software, and the online model simulation of fault diagnosis is realized, and the fault operation performance of complex mechanical system design is understood. The simulation results show that the system can effectively improve the fault diagnosis ability of large mechanical equipment vibration system, realize intelligent fault diagnosis control and adaptive fault treatment, and has good application value in mechanical condition monitoring and other fields.
【作者單位】： 濟源職業(yè)技術(shù)學院;
【分類號】：TH17

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