Cavitation in Rotary Machines

2021 ◽  
pp. 291-310
Author(s):  
Yves Lecoffre ◽  
M.M. Oberai ◽  
V.H. Arakeri
Keyword(s):  
Author(s):  
Min-Chun Pan ◽  
Cheng-Xue Wu

Dynamic signals acquired from rotary machines can be characterized by the order tracking (OT) techniques. The extracted order components correspond to the operation of specific machine elements and reflect their current healthy or faulty states. The study extends the angular-velocity Vold–Kalman OT scheme to simultaneously extract multiple order components. Theoretical derivation is illustrated with simulation of processing three synthetic signals to show its merit. Additionally, as an example to validate its effectiveness, the improved OT scheme is used to process pass-by noise emitted from an electric scooter with a planetary-gear-set transmission system. The gear-meshing orders are effectively decoupled from structure-borne resonances.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2172 ◽  
Author(s):  
Wenjuan Hao ◽  
Yu Wang

Linear flux switching permanent magnetic (LFSPM) machines, with the armature windings and magnets both on the mover in addition to a robust stator, are a good choice for long stoke applications, however, a large cogging force is also inevitable due to the double salient structure, and will worsen the system performance. Skewing methods are always employed for the rotary machines to reduce the cogging torque, and the rotor step-skewed method is a low-cost approximation of regular skewing. The step skewed method can also be applied to the linear machines, namely, the stator step skewed. In this paper, three stator step skewed structures, which are a three-step skewed stator, a two-step skewed stator and an improved two-step skewed stator, are employed for the cogging force reduction of two types of LFSPM machines. The three structures are analyzed and compared with emphasize on the influence of the skewed displacement on the cogging force and the average thrust force. Based on finite element analysis (FEA), proper skewed displacements are selected according to maximum difference between the reduction ratio of the cogging force and the decrease ratio of the average thrust force, then, the corresponding results are compared, and finally, valuable conclusions are drawn according to the comparison. The comparison presented in this paper will be useful to the cogging force reduction of LFSPM machines in general.


Author(s):  
Anand Parey ◽  
Amandeep Singh Ahuja

Gearboxes are employed in a wide variety of applications, ranging from small domestic appliances to the rather gigantic power plants and marine propulsion systems. Gearbox failure may not only result in significant financial losses resulting from downtime of machinery but may also place human life at risk. Gearbox failure in transmission systems of warships and single engine aircraft, beside other military applications, is unacceptable. The criticality of the gearbox in rotary machines has resulted in enormous effort on the part of researchers to develop new and efficient methods of diagnosing faults in gearboxes so that timely rectification can be undertaken before catastrophic failure occurs. Artificial intelligence (AI) has been a significant milestone in automated gearbox fault diagnosis (GFD). This chapter reviews over a decade of research efforts on fault diagnosis of gearboxes with AI techniques. Some of areas of AI in GFD which still merit attention have been identified and discussed at the end of the chapter.


2017 ◽  
Vol 112 ◽  
pp. 180-191 ◽  
Author(s):  
Giuseppe Bianchi ◽  
Sham Rane ◽  
Ahmed Kovacevic ◽  
Roberto Cipollone

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