Abstract
One of the most important aspects in a working machine is the remaining useful life (RUL) of its components. Prognostics in this case depends on establishing the cause-effect entries in the process as well as how it behaves from the series of measures done under experimental conditions. This work introduces two techniques in analyzing series data coming originally from the financial market frame. One of them is the Bollinger Bands theory and another is the Markowitz theory on composite series. Both have a wide spectrum of applications in the cause-effect series prediction.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
S. Sankararaman, Significance, interpretation and quantification of uncertainty in prognostics and remaining useful life prediction. Mech. Syst. Signal Process. 52–53, 228–247 (2015)
J. Bollinger, Bollinger on Bollinger Bands (Mc-Graw Hill, 2001)
W. Liua, X. Huanga, W. Zhenga, Black–Scholes’ model and Bollinger bands. Physica A 371(2), 565–571 (2006)
H.Y.T. Ngan, G.K.H. Pang, Novel method for patterned fabric inspection using Bollinger bands. Opt. Eng. 45(8), 45–56 (2006)
S-C.T. Chou, H.-J. Hsu, C-C. Yang, F. Lai, A stock selection DSS combining AI and technical analysis. Ann. Oper. Res. 75(0), 335–353 (1997)
H. Markowitz, Portfolio selection. J. Finance 7(1), 77–91 (1952)
E.J. Elton, J. Gruber, Theory and Investment Analysis (Wiley, 2005)
B.C. Damasceno, L. Barbanti, Composing a portfolio in stock markets by using a series saturation method. Anais do CNMAC 2, 277–283 (2009)
C. Rowland, J.M. Lawson, The Permanent Portfolio: Harry Browne’s Long-Term Investment Strategy (Wiley, 2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Barbanti, L., Damasceno, B.C., Gonçalves, A.C., Kuzminskas, H. (2017). The Use of Trend Lines Channels and Remaining Useful Life Prediction. In: Ekwaro-Osire, S., Gonçalves, A., Alemayehu, F. (eds) Probabilistic Prognostics and Health Management of Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-55852-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-55852-3_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-55851-6
Online ISBN: 978-3-319-55852-3
eBook Packages: EnergyEnergy (R0)