The vibration quality has been widely used to measure the stability of vehicle operation. In this paper, the healthy condition of the fire robot was determined after the precise Sperling Index of the vibration quality was determined by acceleration and frequency. A method of measuring robot vibration based on virtual instrument technology has also been proposed. The relation between dominant frequency and engine speed has been discussed, and a new divided grades of vibration quality based on the Sperling Index has been found for judging healthy condition of the robot.
SucuogluH.S., The development of fire detection robot, Master Dissertation, Adnan Menderes University, 2015.
2.
FangS.HuB. and LiuS.P., The analysis on fire Smoke exhausting robot vibration based on wavelet transform, Advanced Materials Research328-330 (2011), 1887–1891.
3.
WuQ. and GuJ., Design of robot visual servo controller based on neural network, Journal of Computational Methods in Sciences and Engineering2 (2018), 541–549.
4.
ChenM.Y., Covariance intersection multirobot object tracking algorithm based on self-adaption SR-CKF, Journal of Computational Methods in Sciences and Engineering2 (2018), 479–489.
5.
FangS.LiuS.P. and LiangJ., The design of dynamic vibration absorber on the engine of fire smoke exhausting robot, Applied Mechanics and Materials105-107 (2012), 180–184.
6.
FangS.XuY. et al., The Analysis on Posture Control of Micro Quadrotor Based on PID, International Symposium on Computational Intelligence and Design2 (2012), 283–286.
7.
FangS.LiD.L. et al., Pitting Corrosion diagnosis of bearing based on power cepstrum and histogram, Advanced Materials Research512-515 (2012), 1672–1676.
8.
BruckD. and ThomasI., Interactions between human behaviour and technology, Fire Technology46 (2010), 769–770.
9.
ChenJ., Research on Control Technology of Industrial Robots for Dynamic Performance, Ph.D Dissertation, Harbin Institute of Technology, 2015.
10.
RaoR.M. and BopardikarA.S., Wavelet Transforms: Introduction to Theory and Applications, Prentice Hall PTR, New York, 2004, pp. 61–65.
11.
WangY.M., A brief discussion for ride index and comfort, Railway Locomotive & CAR23(6) (2003), 1–3.
12.
ShaoY.M.ZhouX.J. et al., Extracting Impact Feature of Machine Fault by Using Enhanced Filtering, Journal Of Mechanical Engineering45(4) (2009), 166–172.
13.
BalachandranB.MagrabE.B. and BalachandranA.P., Vibrations, Nelson Engineering, 2002, pp. 11–16.
14.
YangW.X. and JiangJ.S., Study on the singular entropy of mechanical Canal, Chinese Journal of Mechanical Engineering36(12) (2000), 9–13.
15.
HuangN.E.ShenZ. et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of The Royal Society of London Series A Mathematical Physical And Engineering Sciences454 (1998)–903–995.
