Fundamentals of Rotating Machinery Diagnostics

Author(s):  
Bob Grissom ◽  
Charles T. Hatch ◽  
Donald E. Bently
1995 ◽  
Vol 1 (3-4) ◽  
pp. 237-266 ◽  
Author(s):  
Agnes Muszynska

This paper outlines rotating machinery malfunction diagnostics using vibration data in correlation with operational process data. The advantages of vibration monitoring systems as a part of preventive/predictive maintenance programs are emphasized. After presenting basic principles of machinery diagnostics, several specific malfunction symptoms supported by simple mathematical models are given. These malfunctions include unbalance, excessive radial load, rotor-to-stator rubbing, fluid-induced vibrations, loose stationary and rotating parts, coupled torsional/lateral vibration excitation, and rotor cracking. The experimental results and actual field data illustrate the rotor vibration responses for individual malfunctions. Application of synchronous and nonsynchronous perturbation testing used for identification of basic dynamic characteristics of rotors is presented. Future advancements in vibration monitoring and diagnostics of rotating machinery health are discussed. In the Appendix, basic instrumentation for machine monitoring is outlined.


2016 ◽  
Vol 5 ◽  
pp. 1107-1118 ◽  
Author(s):  
Haedong Jeong ◽  
Seungtae Park ◽  
Sunhee Woo ◽  
Seungchul Lee

2001 ◽  
Author(s):  
Jen-Yi Jong ◽  
Wade Dorland ◽  
Tony Fiorucci ◽  
Thomas Zoladz ◽  
Tom Nesman

Author(s):  
Blazˇ Suhacˇ ◽  
Jozˇe Vizˇintin ◽  
Pavle Bosˇkoski ◽  
Dani Juricˇic´

Rotating machines are one of the most wide spread items of equimpnet in the industrial plants; hence the reliable operation is of great practical importance. Analyses show that when a run-to-failure philosophy is adopted in rotating machinery maintenance, their downtime is usually three to four times longer comparing to a periodic or proactive maintenance approach. A successful proactive maintenance program requires an integration of several diagnostic procedures into an intelligent data processing system. Such a system allows detection of a broad range of faults in an early stage. The main aim of this paper is to present current results of our development of an intelligent rotating machinery diagnostics program for detecting a broad range of faults from signals which can be measured non-destructively and on-line. The main motivation is to develop computationally efficient algorithm that can be implemented on a standard (low-cost) platform. In that respect we have developed a test rotating machine equipped with accelerometers, temperature sensors and sensors for lubricating oil characterization. In this paper we focus on gear-box faults and a feature extraction procedure based on non-parametric statistical concepts as suggested and demonstrated on experimental data.


Author(s):  
Amir Shirkhodaie ◽  
Julian Blair ◽  
Kemba Heard

Machinery such as steam turbines, compressors, and generators are rotating machines. Over the years these machines have become very complex, due to the increased need for higher speed rotating machinery. Overtime these machines develop excessive dynamic stresses if they are ran at speeds near to their natural frequencies or under abnormal operating conditions. Many technological advances in the aerospace and automotive industries can be held accountable for these faster speeds. Currently, machinery diagnostics is being used to monitor rotating machinery and determine their condition while in operation. To determine how a system will behave under certain operation conditions, a physics-based model of the system can be modeled and analyzed using finite element analysis. These results will provide stress, deformation, flexibility, stiffness, and vibration characteristics of the system. These results can show where the critical points are on the system and how the system’s load is distributed. By using finite element techniques engineers can simulate the behavior of the system under different loading conditions, which can justify the selection of a particular design alternative, and ultimately save time and money. This paper discusses our technical approach used to develop a physics-based model of a rotor dynamic system and discusses results of this research effort.


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