本文關(guān)鍵詞： 船舶動(dòng)力系統(tǒng) 故障診斷 專家系統(tǒng) SOM 神經(jīng)網(wǎng)絡(luò) 趨勢(shì)預(yù)測(cè)　出處：《武漢理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：船舶動(dòng)力系統(tǒng)作為整個(gè)船舶的心臟與動(dòng)脈，包括主推進(jìn)裝置、輔助供能裝置、用于保證船舶安全運(yùn)行的設(shè)備、滿足船員正常生活的設(shè)備和環(huán)境保護(hù)設(shè)備等。由于船舶動(dòng)力系統(tǒng)的運(yùn)行條件苛刻，并具有強(qiáng)烈的時(shí)變性，一旦發(fā)生故障，往往會(huì)造成嚴(yán)重的后果，其安全可靠的運(yùn)行將直接影響到船舶運(yùn)行的安全。在船舶動(dòng)力系統(tǒng)趨于自動(dòng)化和智能化的背景下，對(duì)船舶動(dòng)力系統(tǒng)進(jìn)行智能化故障診斷是保證該系統(tǒng)安全可靠運(yùn)行的重要方法之一，具有重要意義。 本文在分析國(guó)內(nèi)外船舶動(dòng)力系統(tǒng)故障診斷系統(tǒng)的發(fā)展現(xiàn)狀的基礎(chǔ)上，針對(duì)目前存在的在線診斷能力薄弱等問題，研究了船舶動(dòng)力系統(tǒng)智能故障診斷方法。首先采用規(guī)則引擎技術(shù)，研究了船舶動(dòng)力系統(tǒng)故障診斷專家系統(tǒng)的推理方式以及診斷規(guī)則庫(kù)的構(gòu)建，制定了以Drools為推理引擎的專家系統(tǒng)方案。通過對(duì)船舶動(dòng)力系統(tǒng)的主要故障模式進(jìn)行分析總結(jié)，以此為基礎(chǔ)構(gòu)建診斷知識(shí)庫(kù)。為解決專家系統(tǒng)在實(shí)施過程中存在的知識(shí)獲取瓶頸、不完整性信息處理能力較差等問題，進(jìn)行了數(shù)據(jù)驅(qū)動(dòng)的故障診斷方法的研究，并通過SOM神經(jīng)網(wǎng)絡(luò)構(gòu)建故障診斷模型來彌補(bǔ)專家系統(tǒng)的不足。同時(shí)，為了實(shí)現(xiàn)事后診斷向預(yù)診斷方式的轉(zhuǎn)變，在故障診斷的基礎(chǔ)上，研究了船舶動(dòng)力系統(tǒng)主要狀態(tài)參數(shù)的趨勢(shì)預(yù)測(cè)方法，，采取了ARMA模型和小波神經(jīng)網(wǎng)絡(luò)模型。在對(duì)比兩種模型的特點(diǎn)和適用范圍的基礎(chǔ)上，針對(duì)不同的狀態(tài)參數(shù)選取不同的模型進(jìn)行了趨勢(shì)預(yù)測(cè)，可以實(shí)現(xiàn)對(duì)異常參數(shù)變化的提前報(bào)警，對(duì)船舶動(dòng)力系統(tǒng)的日常維護(hù)具有一定的指導(dǎo)意義。 本文以“東海救117”為應(yīng)用對(duì)象，在原有船舶動(dòng)力系統(tǒng)狀態(tài)監(jiān)測(cè)系統(tǒng)的基礎(chǔ)上，利用該系統(tǒng)采集的船舶動(dòng)力系統(tǒng)狀態(tài)參數(shù)進(jìn)行故障診斷。根據(jù)對(duì)故障診斷方法以及趨勢(shì)預(yù)測(cè)技術(shù)的研究，對(duì)故障診斷系統(tǒng)的功能進(jìn)行了設(shè)計(jì)，對(duì)其實(shí)現(xiàn)方法進(jìn)行了研究。以Windows操作平臺(tái)為運(yùn)行平臺(tái)，Java為開發(fā)語言，利用Eclipse作為開發(fā)工具完成了故障診斷專家系統(tǒng)功能的實(shí)現(xiàn)，為輪機(jī)工作人員對(duì)船舶動(dòng)力系統(tǒng)的維護(hù)提供了一種新手段。
[Abstract]:Ship power system as the whole ship's heart and artery, including the main propulsion device, auxiliary energy supply device, used to ensure the safe operation of the ship equipment. Because of the harsh operating conditions of the ship's power system and its strong time-varying characteristics, once it breaks down, it will often cause serious consequences. Its safe and reliable operation will directly affect the safety of ship operation. Intelligent fault diagnosis of ship power system is one of the important methods to ensure the safe and reliable operation of the system. Based on the analysis of the development of fault diagnosis system for marine power system at home and abroad, this paper aims at the existing problems such as weak on-line diagnosis ability and so on. The intelligent fault diagnosis method of ship power system is studied. Firstly, the reasoning method of fault diagnosis expert system of ship power system and the construction of diagnosis rule base are studied by rule engine technology. An expert system scheme with Drools as the inference engine is developed, and the main fault modes of ship power system are analyzed and summarized. In order to solve the problems such as the bottleneck of knowledge acquisition and the poor processing ability of incomplete information, the data-driven fault diagnosis method is studied. The fault diagnosis model is constructed by SOM neural network to make up for the deficiency of expert system. At the same time, in order to realize the transformation from post-diagnosis to pre-diagnosis, it is based on fault diagnosis. The trend prediction method of the main state parameters of ship power system is studied. The ARMA model and the wavelet neural network model are adopted, and the characteristics and applicable scope of the two models are compared. According to different state parameters, different models are chosen to predict the trend, which can alarm the abnormal parameters in advance, and have certain guiding significance for the daily maintenance of ship power system. This paper takes "Donghai Rescue 117" as the application object, on the basis of the original ship power system condition monitoring system. According to the research of fault diagnosis method and trend prediction technology, the function of fault diagnosis system is designed. The implementation method is studied. The Windows operating platform is used as the operating platform and the Java language is used as the development language. The function of fault diagnosis expert system is realized by using Eclipse as a development tool, which provides a new method for the maintenance of marine power system.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U664.81;U672.74

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