Experimental Investigation Using Response Surface Methodology for Condition Monitoring of Misaligned Rotor System

2021 ◽  
pp. 1-9
Author(s):  
Shital Patil ◽  
Arun K Jalan ◽  
Amol Marathe
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
System Performance ◽  
Significant Variation ◽  
Vibration Amplitude ◽  
Axial Direction ◽  
Response Factor ◽  
Rotating System ◽  
Remarkable Effect ◽  
System Vibration

Abstract Misalignment is one of the key reasons for vibrations in most of the rotating system. The present work focuses on interactions between speed, load, and defect severity by investigating their effect on the system vibration. Response Surface Methodology (RSM) with Root Mean Square (RMS) as a response factor is used to understand the influence of such interactions on the system performance. Experiments are planned using design of experiments and analysis is carried out using Analysis of Variance (ANOVA). It is observed that, speed has a remarkable effect on RMS value in both parallel and angular type of misalignment and affects the system performance. RSM results revealed that a change in load has less impact on vibration amplitude in case of horizontal and vertical directions but there is significant variation in RMS value in axial direction for both type of misalignment. A slight increase in RMS value with increase in defect severity is observed in axial direction. These observations will help to understand the misalignment defect and its effect in a better way.

Modeling and Optimization of Vibration Amplitude in Turning of Ti-6Al-4V Using Response Surface Methodology

2012 ◽  
Vol 217-219 ◽  
pp. 1567-1570
Author(s):  
A.K.M. Nurul Amin ◽  
Muammer Din Arif ◽  
Syidatul Akma Sulaiman
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Vibration Amplitude ◽  
Desirability Function ◽  
Cutting Speed ◽  
Vibration Sensor ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Work Piece ◽  
Inferior Surface

Chatter is detrimental to turning operations and leads to inferior surface topography, reduced productivity, dimensional accuracy, and shortened tool life. Avoidance of chatter has mostly been through reliance on heuristics such as: limiting material removal rates or selecting low spindle speeds and shallow depth of cuts. But, modern industries demand increased output and not steady operational limits. Various research efforts have therefore focused on developing mathematical models for chatter formation. However, as yet there is no existent model that meets all experimental verification. This research employed a novel technique based on the synergy of statistical modeling and experimental investigations in order to develop an effective empirical mathematical model for chatter amplitude and to subsequently find optimal machining conditions. Ti-6Al-4V, Titanium alloy, was used as the work-piece due to its increased popularity in applications related to aerospace, automotive, nuclear, medical, marine etc. A sequence of 15 experimental runs was conducted based on a small Central Composite Design (CCD) model in Response Surface Methodology (RSM). The primary (independent) parameters were: cutting speed, feed, and depth of cut. The tool overhang was kept constant at 70 mm. An engine lathe (Harrison M390) was employed for turning purposes. The data acquisition system comprised a vibration sensor (accelerometer) and a signal conditioning unit. The resultant vibrations were analyzed using the DASYLab 5.6 software. The best model was found to be quadratic which had a confidence level of 95% (ANOVA) and insignificant Lack of Fit (LOF) in Fit and Summary analyses. Desirability Function (DF) approach predicted minimum vibration amplitude of 0.0276 Volts and overlay plots identified two preferred machining regimes for optimal vibration amplitude.

Surface Roughness Model for Helical Milling of Die-Steel Based on Response Surface Methodology

2010 ◽  
Vol 431-432 ◽  
pp. 346-350 ◽  
Author(s):  
Xu Da Qin ◽  
Song Hua ◽  
Xiao Lai Ji ◽  
Shi Mao Chen ◽  
Wang Yang Ni
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Axial Direction ◽  
Helical Milling ◽  
Design Parameters ◽  
Die Steel ◽  
Roughness Model ◽  
Milling Operation ◽  
Hole Making

Holes making process is widely applied in die steel machining, Helical milling a hole, also called orbital drill, is hole making process by milling in which the center of end mill orbits around the center of the hole while spinning on its axis and moving in the axial direction. The paper presents the secondary regression prediction model of the holes surface roughness for helical milling of die-steel. To minimize the number of experiments for the design parameters, response surface methodology (RSM) with orthogonal rotatable central composite design is used. By means of variance analyses and additional cutting experiments, the adequacy of this model is confirmed. The model will be helpful in selecting cutting conditions to meet surface finish requirements in helical milling operation.

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