پديد آورنده :
احمدي پاريزي، حميد
عنوان :
پايش وضعيت ماشين آلات دور پايين با استفاده از آزمون پخش آوا
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
طراحي كاربردي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك
صفحه شمار :
چهارده،100ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
مصطفي غيور
استاد مشاور :
سعيد ضيايي راد
توصيفگر ها :
ماشين آهسته گرد , تبديل موجك , بيرينگ غلتشي , اصطكاك ضربه , كورتوسيس
تاريخ نمايه سازي :
13/12/92
استاد داور :
حميدرضا ميردامادي، رضا تيكني
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Condition Monitoring of Slow Speed Machines with the use of Acoustic Emission Test Hamid Ahmadi Parizi Hamid ahmadi@me iut ac ir Date of submission 2014 01 18 Department of mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language PersianSupervisor Dr Mostafa Ghayour ghayour@cc iut ac irAbstractNowadays condition monitoring CM techniques have prepared facility to optimize maintenancesystems CM includes some methods that vibration test is the most important method for rotationalmachines CM of slow speed machines is challenging to the various industries because they areoften the most important machines in the production lines On the other hand CM of them is notachieved by the vibration test In the recent years several studies are carried out by acousticemission AE techniques to measure and analyze physical wave produced by slow speedmachines Since the AE wave is created by variation of the tension and the microscopic strain inmaterial or on its surface some defects like friction and impact produce AE waves independent ofrotational speed So we have an applied method for fault detection of slow speed machines Thisresearch focuses on the fault detection of rolling element bearings because they are used in the vastmajority of slow speed machines and most sensitive parts to be damaged Finally AE techniquesare able to detect creation and progress of their fault In this research the AE phenomenon and propagation principles producer objects in machinery data measurement indication and processing methods fault detection of rolling element bearingsand artificial neural network are studied Experimental tests are then done In the first step a test rigis subjected to AE test after that two slow speed machines in Mobarakeh Steel Complex are testedand analyzed In this thesis it is cleared that if a slow speed is periodically tested and analyzed byusing AE techniques and gathering data is processed by a suitable wavelet transform then statisticalparameters specifically kurtosis are calculated and their trends are observed we can realize faultprogress of the machine and detect type of the defects with the use of envelop function It is alsoobserved if an artificial neural network is correctly designed for a machine prediction of the failureintensity is achievable by using AE data Additionally friction and impact phenomenon in the damaged slow speed bearings are studied Previous research done with the use of test rig shows friction falls between 50 kHz to 100 kHz Here this is ascertained for an industrial machine Relation to impact phenomenon it is cleared thatnatural frequency of AE sensor is able to be excited and dominant frequency of wave happens inthe range of natural frequency of the sensor Keywords Condition monitoring Acoustic emission Slow speed machines Wavelet transform Rolling element bearing Friction Impact Kurtosis
استاد راهنما :
مصطفي غيور
استاد مشاور :
سعيد ضيايي راد
استاد داور :
حميدرضا ميردامادي، رضا تيكني
