機(jī)械監(jiān)測診斷中的理論與方法

前言

屈梁生是中國工程院院士、西安交通大學(xué)教授、博士生導(dǎo)師。他工952年于交通大學(xué)機(jī)械系畢業(yè)，留校任教；后隨校遷往西安，長期任教于西安交通大學(xué)。屈梁生院士長期從事機(jī)械質(zhì)量控制與監(jiān)測診斷領(lǐng)域的基礎(chǔ)性與開拓性研究。他把信息論、系統(tǒng)論的原理融入到機(jī)械故障診斷和狀態(tài)監(jiān)測中去，從整體上提升了這一傳統(tǒng)學(xué)科。屜梁生院士的研究課題來自生產(chǎn)實(shí)踐，在提升為理論后，再放回到實(shí)踐中去考驗(yàn)，然后又反過來再推動(dòng)理論進(jìn)一步完善提高。這種不斷反復(fù)的精神貫穿在他整個(gè)科研工作中。他在科研方法論中不受傳統(tǒng)與成見的束縛，獨(dú)具慧眼，不斷開拓出新的領(lǐng)域。典型的一個(gè)實(shí)例是，在已成熟并已廣泛應(yīng)用的FFT技術(shù)中加入相位信息，將多個(gè)傳感器的振動(dòng)信號(hào)在頻域中合成，提出了這個(gè)由中國人始創(chuàng)的“全息譜”理論，大大地提高了FFT的水平，擴(kuò)大了其工作范圍。屈梁生教授在注意提高學(xué)生的理論知識(shí)與獨(dú)立工作能力的同時(shí)，也十分注意培養(yǎng)他們的道德修養(yǎng)。他認(rèn)為，作為新一代的科技人員，首先應(yīng)該是一個(gè)具有高尚品德的人。記得有一次我與他談起科研工作中出現(xiàn)的浮躁情緒及帶來的種種弊端時(shí)，都感到不斷提高自身的修養(yǎng)，才能耐得住寂寞，長期堅(jiān)持，出真正的成果。由此還談到李叔同的名言：“事能知足心常樂，人若無求品自高”，詠之感嘆再三，相互勉勵(lì)。這本論文集是屈梁生教授一生科研工作的總結(jié)，是留給后人的一筆財(cái)富?？萍及l(fā)展無止境，在他的基礎(chǔ)上進(jìn)一步發(fā)展提高，才是出本論文集的更高期望。

內(nèi)容概要

　　《機(jī)械監(jiān)測診斷中的理論與方法（屈梁生論文集）》全文收錄了中國工程院院士屈梁生的166篇高水平論文。內(nèi)容涉及全息譜、全息動(dòng)平衡、獨(dú)立分量／主分量、質(zhì)量保障與優(yōu)化、小波分析、遺傳算法、貝葉斯網(wǎng)絡(luò)、支持向量機(jī)、模糊理論、神經(jīng)網(wǎng)絡(luò)、專家系統(tǒng)、監(jiān)測預(yù)報(bào)、Wigner分布、噪聲抑制、回歸分析、信息化生產(chǎn)、粗糙集、決策表／決策樹、循環(huán)統(tǒng)計(jì)、統(tǒng)計(jì)模擬、EMD、故障診斷理論與方法等。另附有345篇論文的總篇目、論文主題索引和研究對(duì)象索引三個(gè)附錄?！　　稒C(jī)械監(jiān)測診斷中的理論與方法（屈梁生論文集）》適合大學(xué)相關(guān)專業(yè)的教師、研究生，以及從事機(jī)械故障診斷研究的科研人員閱讀。

書籍目錄

屈梁生院士簡介序機(jī)床自動(dòng)停刀機(jī)構(gòu)精度的研究熱變形對(duì)導(dǎo)軌磨削精度的影響計(jì)量光柵的幾何、光學(xué)特性評(píng)幾項(xiàng)超微米技術(shù)的進(jìn)展自回歸譜在機(jī)器故障診斷中的應(yīng)用時(shí)間序列分析在機(jī)器狀態(tài)識(shí)別中的應(yīng)用On—line Surveillance of Process Equipment Using Autoregressive Feature Extraction and Walsh TransformationKULLBACK—LEIBLER信息數(shù)在識(shí)別機(jī)器振動(dòng)信號(hào)功率譜中的應(yīng)用An ExDerimental Research on Optical Fiber Sensor and Its Application to the Grinding Process Supervision機(jī)器故障診斷技術(shù)及其現(xiàn)狀與展望The Evaluation of Low—Frequency Knock of Precise Gearbox Via Spectra Distance Measure Autoregressive Cepstrum and Its Application in Noise Diagnosis of GearboxesOn—line Surveillance of a Grinding Process Via a Kullback—Leibler Information Number Statistical Control of Low Frequency Knock in Machine Tool Gearbox Production光纖傳感器及其在磨削過程監(jiān)測中的應(yīng)用The Thermal Behavior of Machine Tool GuidwaysThe Application of Maximum Entropy Spectrum in Analysis of the Accuracy 0．f Precision Gear Transmission The Evaluation of Low—frequency Knock in the Gearbox of Modern Machine Tools Friction Failure Diagnosis of Steam Turb0—Generator Sets Via Principal Components andAutoregressive TechniqueGrinding Process Supervision Via Information Distance Measure A New Approach to Computer—aided Vibration Surveillance of Rotating Machinery Discovering the HolospectrumThe H010spectrum：A New Method for Rotor Surveillance and Diagnosis 專家系統(tǒng)中知識(shí)一致性和完備性檢驗(yàn)的一種方法The Holospectrum：A New FFT Based Rotor Diagnostic MethodA New Me!thod Evaluating Operating Condition for Rotating MachineryTime—frequencv Distributions of Vibration Signals in Rotating Machinery A Rule—based ExPert System for Real—Time Gear—manufacturing Process Control 回轉(zhuǎn)機(jī)械振動(dòng)頻譜的模糊分類及應(yīng)用The Phase Information in the Rotor Vibration Behaviour Analysis Investigation of the Special Trending Method for Rotating Machinery Monitorin9Rotating MachineRy Fault Diagnosis Using wigner Distri bution全息譜分析方法的原理和應(yīng)用神經(jīng)網(wǎng)絡(luò)在大型回轉(zhuǎn)機(jī)械故障診斷中的應(yīng)用全息譜技術(shù)用于化工廠機(jī)械故障診斷機(jī)械監(jiān)測診斷中的譜距分類與預(yù)報(bào)大型機(jī)組診斷信息的深層次處理問題IntelugentConntro1 oftheGear—Shaving Process轉(zhuǎn)子徑向摩擦故障診斷技術(shù)的研究HomoSourCe ANC and Its Application to the Machinery DiagnosisStudV and PerformanCe Evaluation of Some Nonlinear Diagnostic：Methods for．Large Rotating Machineryorbit Corrlplexity：A New Criterion for Evaluating the Dynamk：QuantyofRotorsystems齒輪聯(lián)軸節(jié)對(duì)中不良振動(dòng)信息研究Fault Prognosis for Large Rotating Machinery Using Neural Net work基于二維全息譜的回轉(zhuǎn)機(jī)械亞同步振動(dòng)分析Vibrational Diagnosis of Machine Parts Using the wavelet．：Packet Technique轉(zhuǎn)子橫向裂紋振動(dòng)診斷技術(shù)的研究談?wù)剻C(jī)組故障的可診斷性問題談?wù)剻C(jī)組故障的可診斷性問題(續(xù))小波包原理及其在機(jī)械故障診斷中的應(yīng)用Somc Analvtical Problems of High Performance Flexm．e Hinge and Micro—mot：ion Stage Design The Prognosis of Vibration Condition for a 200 MW Turbo—Generator Set Using Anificial NeuralNetworkThe Noise Suppression Chain—A New Approach to Time Series Preprocessmg共軛梯度神經(jīng)網(wǎng)絡(luò)的研究機(jī)械故障診斷技術(shù)與當(dāng)代前沿科學(xué)(一)機(jī)械故障診斷技術(shù)與當(dāng)代前沿科學(xué)(二)機(jī)械故障診斷技術(shù)與當(dāng)代前沿科學(xué)(三)小波分析的工程理解及其在機(jī)械診斷中的應(yīng)用小波包的移頻算法與振動(dòng)信號(hào)處理柔性轉(zhuǎn)子鍵相信號(hào)初始相位及振動(dòng)信號(hào)相位的確定TeSt SCquencing and Diagnosis in Electronic System withDecision Table大型回轉(zhuǎn)機(jī)械故障的組合網(wǎng)絡(luò)識(shí)別方法基于神經(jīng)網(wǎng)絡(luò)的喘振早期發(fā)現(xiàn)Predicting Grinding Burn Using Artificial Neural Networks非線性動(dòng)力系統(tǒng)理論在機(jī)械故障診斷中的應(yīng)用基于信息優(yōu)化的前饋神經(jīng)網(wǎng)絡(luò)及其應(yīng)用人工神經(jīng)網(wǎng)絡(luò)與機(jī)械工程中的智能化問題全息譜的分解及其在機(jī)械診斷中的應(yīng)用多分辨小波網(wǎng)絡(luò)的理論及應(yīng)用小波分析及其在機(jī)械診斷中的應(yīng)用The Fauh Recognition Problem in Engineering Diagnost icsFractal Geometry Used for Chartactcrization of Grinding wheel Profiles全息動(dòng)平衡技術(shù)：原理與實(shí)踐多平面平衡中平衡面相關(guān)問題的處理全息譜力、力偶分解法在全息動(dòng)平衡中的應(yīng)用Optimization of the Measuring Path on a Coordinate Measuring Machine Using Genetic Algorithms機(jī)械診斷中的故障識(shí)別問題平穩(wěn)熵：一種新的機(jī)組運(yùn)行瞬時(shí)穩(wěn)定性定量化監(jiān)測指標(biāo)轉(zhuǎn)子橫向裂紋故障的診斷信息提取大機(jī)組振動(dòng)信號(hào)復(fù)雜性的定量描述截尾奇異值分解技術(shù)在動(dòng)平衡中的應(yīng)用三維全息譜分解在回轉(zhuǎn)機(jī)械診斷中的應(yīng)用研究回轉(zhuǎn)機(jī)械診斷信息的集成：全息譜技術(shù)十年基于主分量分析的噪聲壓縮技術(shù)研究全息譜十年：回顧與展望轉(zhuǎn)子動(dòng)平衡中的相關(guān)平衡面問題基于扭振信號(hào)的齒輪故障診斷研究Intelligent Method for Online Vibration MonitoringA Soft Computing Based Approach for Multisensor Data FusionFeaturc Extraction Using Continuous WaveletTransform and Its Application for Mechanical Fault Diagnosis基于概率神經(jīng)網(wǎng)絡(luò)的機(jī)組狀態(tài)多步預(yù)報(bào)方法A Difference Resonator for Detecting weak SignalsA Synergetic Approach to Genetic Algorithms for Solving Traveling Salesman ProblemA Genetic Algorithm Based Balancing Framework for Flexible RotorsOne Decade of Holospectral Technique：Review and Prospect小波分析及其在壓縮機(jī)氣閥故障檢測中的應(yīng)用研究改進(jìn)的決策樹生成算法及條件決策表的創(chuàng)建基于概率神經(jīng)網(wǎng)絡(luò)的大機(jī)組組合故障識(shí)別一種改進(jìn)的隨機(jī)減量信號(hào)提取方法Feature Extraction Based on Morlet Wavelet and Its Application for Mechanical Fault Diagnosis機(jī)械診斷中的幾個(gè)基本問題遺傳算法進(jìn)化截止代數(shù)分布規(guī)律的研究非對(duì)稱轉(zhuǎn)子的全息動(dòng)平衡技術(shù)The OptimizationTechnique－Based Balancing of Flexible Rotors Without Test Runs基于影響系數(shù)法的柔性轉(zhuǎn)子無試重平衡法研究遺傳算法優(yōu)化效率的定量評(píng)價(jià)A Reduction Method of Rough Set Model遺傳算法在故障特征選擇中的應(yīng)用研究應(yīng)用連續(xù)小波變換提取機(jī)械故障的特征基于連續(xù)小波變換的信號(hào)檢測技術(shù)與故障診斷神經(jīng)網(wǎng)絡(luò)在轉(zhuǎn)子動(dòng)平衡中應(yīng)用的幾個(gè)關(guān)鍵問題A New Practical Modal Method for Rotor Balancing柔性彎曲轉(zhuǎn)子的特征識(shí)別與診斷Instantaneous Purified Orbit：A New TOol for Analysis of Nonstationary Vibration of Rotor SystemUsing Continuous Wavelet Transform to Detect Impact Component in Machine Fault Diagnosis機(jī)器振動(dòng)診斷中信號(hào)處理方法的研究Extracting the Characteristic Frequency from Vibration Signal of Rolling Bearing with Self—OrganizinMetbodPartially Blind Source Separation of the Diagnostic Signals with Prior Knowledge提高故障診斷質(zhì)量的幾種方法Machine Diagnosis with Independent Component Analysis and Envelope Analysis應(yīng)用Bootstrap方法構(gòu)造機(jī)械故障特征庫機(jī)械信號(hào)連續(xù)小波系數(shù)的統(tǒng)計(jì)特征研究提取機(jī)械信號(hào)中弱沖擊成分的研究遺傳編程在無量綱指標(biāo)構(gòu)建中的應(yīng)用Some Applications of Statistical Simulation in Engineering Diagnostics基于小波變換和支持向量機(jī)的人臉檢測系統(tǒng)自適應(yīng)閾值選擇和小波消噪方法研究應(yīng)用獨(dú)立分量分析提取機(jī)器的狀態(tài)特征汽車發(fā)動(dòng)機(jī)診斷的統(tǒng)計(jì)模擬方法故障診斷中多傳感器信息冗余性的研究循環(huán)統(tǒng)計(jì)量方法在滾動(dòng)軸承故障診斷中的應(yīng)用Application of Wavelet Packet Analysis for Fault Detection in Electro—Mechanical Systems Based on Torsional Vibration Measurement基于冗余信息量的設(shè)備行為可預(yù)測性的研究Enhanced Diagnostic Certainty Using Information Entropy TheoryCyclic Statistics in Rolling Bearing Diagnosis一種貝葉斯診斷網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu)貝葉斯網(wǎng)絡(luò)推理的一種仿真算法基于遺傳編程和支持向量機(jī)的故障診斷模型二代小波消噪在數(shù)字信號(hào)處理器中的實(shí)時(shí)實(shí)現(xiàn)應(yīng)用全息譜技術(shù)診斷熱變形不均勻引起的振動(dòng)故障回轉(zhuǎn)機(jī)械故障診斷中的三維全息譜技術(shù)機(jī)械產(chǎn)品的信息化——面向機(jī)械裝備的信息技術(shù)全息譜技術(shù)在現(xiàn)場動(dòng)平衡前故障診斷中的應(yīng)用機(jī)械故障診斷的推理規(guī)律研究Translation—Invariant Based Adaptive Threshold Denoising for Impact Signal基于混沌和符號(hào)序列統(tǒng)計(jì)的滾動(dòng)軸承故障診斷Discussion Authors ReplyA Rapid Response Intelligent Diagnosis Network Using Radial Basis Function NetworkApplication of Adaptive Neuro—Fuzzy Inference System in Field BalancingA nonlinear Diagnosis Method of Gear Early Fatigue CrackSigmoid Model：A Simulation for Inference Process of Engineering Diagnosis齒輪早期疲勞裂紋的混沌檢測方法An Improved Independent Component Analysis algorithm and Its Application in Preprocessing of Bearing soundsA New Time Series Forecasting Approach Based on Bayesian Least Risk PrincipleA genetic Algorithm Based Balancing Framework for Flexible RotorsApplications of Chaotic Oscillator in Machinery Fault Diagnosisz息動(dòng)平衡原理A New Field Balancing Method of Rotor Systems Based on Holospectrum and Genetic AlgorithmDiagnosis of Subharmonic Faults of Large Rotating Machinery Based on EMD……附錄

章節(jié)摘錄

插圖：INTRODUCTIONNowadays，the grinding operation is one of the mostimportant metal processing methods.The per.formance and reliability of modem machine productsare seriously influenced by the surface perfection.dimensiona！and geometrical accuracies of their ele.ments.the majority of which are finished bv digfferentkinds of grinding operations.In modem automaticgrinders it is quite necessary to adopt the on.1inesurveillance via dynamic signal recognition in orderto prevent the degradation and deterioration ofworkpieces as the result of wheel wear andlOSS of itscutting ability.In general，the wheel life between twosucceeding turning operations is characterized by thevariation of grinding sound，increase of grindingforces and the violence of grinding chatter。which canbe easily recognized by experienced operators.Butwith regard to the automatic in-process recognitionof these signals the closest attention js now solicitedin order to monitor the performance of wheelandgrinder under different grinding conditions and toprognosticate the remaining wheel lift.In this paper.a new criterion called the Kullback-Leibler informa.tion humber based on time.series analysis and infor.mation theory is suggested to monitor the per.formance of whee！and grinder under difierentworking conditions and to prognosticate the remain.ing wheel life.The computer flow chart for supc-vision of the grinding cycles is also designed andtested.PROCEDURE  The main aspccts for on.1ine surveillance of agrinding process by means of the Kullback-Leiblerinformation humber are as follows：（1）measurementof the dynamic signals emitted in difierent stages ofgrinding process between two succeeding trueingoperations；（2）A／D conversion.of each signal to formthe corresponding discrete time series；（3）establish.ement of the reference models.These models can beautoregressive moving average（ARMA）models orsimplified autoregressive（AR）models[1]；（4）storageof the information about these reference modelsin computer memory.i.e.the values of modelcoefficients as well as the residua！varianoe of eachmodel.The more reference models are stored，thebetter recognition capability the computer will pos.sess；（5）modelling the current tested signal in grind.ing operation and calculation of the Kullback-Leibler information numbers between this new modeland each reference model already stored in computer；（6）assignment of the tested signal to the category ofone of the reference models with minimum valuesof the KullbacLLeibler number.The computerflowchart is shown in Fig.l.Its performance is todecide which reference model the tested sequenceshould belong to，and to establish new referencemodels.That is to say，the software pOSSeSSeS theself-learning ability and can improve the recognitioncapability of computer.ExPERHMENTATION  The experiments were carded out using an ordi.nary cylindrica！grinder with hydrostatic main bear.ings.The materials taken for testpieces were hard.ened carbon steels marked 45.55 and T8 withhardness from R=40 to 60 and diameters from 035to 85 mm.A grinding whee！of GB46ZR2SP.e500 x 40 x 305 mm and ordinary emulsion fluidwere selected.In experiments.the testpieces were fedradially to the wheel without transverse feed.Thcnormal and tangential grinding forces，vibrationaldisplacement 0f a specia！designed dead centre andgrinding sound were measured by the eddy currenttransducer，  dynamic strain gauges and precisionsound level meter accordingly as shown in Fig.

編輯推薦

《機(jī)械監(jiān)測診斷中的理論與方法》適合大學(xué)相關(guān)專業(yè)的教師、研究生，以及從事機(jī)械故障診斷研究的科研人員閱讀。

圖書封面

評(píng)論、評(píng)分、閱讀與下載

---

    機(jī)械監(jiān)測診斷中的理論與方法 PDF格式下載

---