Rotating Machinery and Controls Laboratory
نویسنده
چکیده
منابع مشابه
A Novel Intelligent Fault Diagnosis Approach for Critical Rotating Machinery in the Time-frequency Domain
The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...
متن کاملBearing Fault Detection Based on Maximum Likelihood Estimation and Optimized ANN Using the Bees Algorithm
Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...
متن کاملVibration Based Condition Monitoring in Rotating Machineries
In Chapters 15 and 16, the measurement and signal processing techniques, transducers, signal conditioners and signal analysis equipments are described, which are used in the rotating machinery condition monitoring. It is very important to display the measured signal in convenient form so as to be useful for the interpretation of the condition of rotating machinery. In the present chapter, by lo...
متن کاملBoundary Layers and Heat Transfer on a Rotating Rough Disk
The study of flow and heat transfer over rotating circular disks is of great practical importance in understanding the cooling of rotatory machinery such as turbines, electric motors and design and manufacturing of computer disk drives. This paper presents an analysis of the flow and heat transfer over a heated infinite permeable rough disk. Boundary-layer approximation reduces the elliptic Nav...
متن کاملCondition Surveillance for Plant Rotating Machinery Using a Fuzzy Neural Network
Abstract—Condition surveillance of rotating machinery in a plant is very important for guaranteeing production efficiency and plant safety. In a large plant, because there are an enormous number of rotating machines, condition surveillance for all rotating machines is time consuming and labor intensive and the accuracy of condition judgment is not ensured. These difficulties may cause serious m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003