**7. References**


**Part 2** 

**Telemetry Data Mining**


**Part 2** 

**Telemetry Data Mining**

92 Modern Telemetry

Mascarenas, D.L., Park, G., Farinholt, K., Todd, M.D. and Farrar, C.R. (2009). A low-power

Mehta, P. K. and Monterio, P. J. M. (Sep 30, 2005). *Concrete: microstructure, properties, and* 

Min, J., Park, S., Yun, C.-B., and Song, B. (2010). Development of Low-cost Multi-functional

Overly, T.G., Park, G., Farrar, C.R. and Allemang, R.J. (2007). Compact hardware

Overly, T.G., Park, G., Farinholt, K.M. and Farrar, C.R. (2008). Development of an extremely

Park, G., Cudney, H. H. and Inman, D. J. (2000), Impedance-based health monitoring of civil

Park, G., Sohn, H., Farrar, C.R. and Inman, D.J. (2003). Overview of piezoelectric impedance-

Park, G., Farrar, C.R., Rutherford, A.C. and Robertson, A.N. (2006). Piezoelectric active

Park, S., Ahmad, S., Yun, C.-B., and Roh, Y. (2006). Multiple Crack Detection of Concrete

Park, S.,, Kim, J.-W., Lee, C.-G., and Park, S.-K. (2011). Impedance-based Wireless

Park, S., Shin, H.H. and Yun, C.B. (2009), Wireless impedance sensor nodes for functions of

Park, S., Yun, C.-B., and Roh, Y. , and Lee, J.-J. (2005). Health monitoring of steel structures

Shariq, M., Parasad, J. and Masood, A. (2010). Effect of GGBFS on time dependent

Taylor, S.G., Farinholt, K.M., Park, G. and Farrar, C.R. (2009a). Wireless impedance device

Talyor, S.G., Farinholt, K.M., Flynn, E.B., Figueiredo, E., Mascarenas, D.L., Moro, E.A., Park,

*Vibration and Acoustics*, Vol. 128, No. 4, pp. 469-476, ISSN 10489002

*Journal of Experimental Mechanics*, Vol. 46, pp.609-618.

*Structures*, Vol. 18, No. 5, 055001, ISSN 09641726

*materials. 3rd ed.*, McGraw-Hill, ISBN 0071462899, New York,

*on Structural Dynamics*, Orlando, FL, February 2007.

Vol. 17, No. 6., 065011, ISSN 09641726

160, ISSN 10760342

6, pp. 451-463, ISSN 05831024

*International*, Vol. 44, pp. 232-238

*Systems*, Vol. 1, No. 4, pp.339-353.

081947552-7, San Diego, CA, March 2009

Vol. 20, No. 4, 045201, ISSN 09570233

pp. 1469-1478, ISSN 09500618

No. 5, pp. 565-575, ISSN 09544100

689-709

wireless sensing device for remote inspection of bolted joints, *Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering*, Vol. 223,

Wireless Impedance Sensor Nodes, *Smart Structures and Systems*, Vol. 6, No. 5-6 pp.

development for structural health monitoring and sensor diagnostics using admittance measurements, *Proceedings of the IMAC-XXV: A Conference & Exposition* 

compact impedance-based wireless sensing device, *Smart Materials and Structures*,

structural components, *Journal of Infrastructure and Systems,* Vol. 6, No. 4, pp.153-

based health monitoring and path forward, *Shock and Vibration Digest*, Vol. 35, No.

sensor self-diagnostics using electrical admittance measurements, *Journal of* 

Structures Using Impedance-based Structural Health Monitoring Techniques,

Debonding Condition Monitoring of CFRP Laminated Concrete Structures, *NDT&E* 

structural damage identification and sensor self-diagnosis, *Smart Materials and* 

using impedance of thickness modes at PZT patches, *Journal of Smart Structures and* 

compressive strength of concrete, *Construction and Building Materials,* Vol. 24, No. 8

for electromechanical impedance sensing and low-frequency vibration data acquisition, *Proceedings of the SPIE Annual International Symposium on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems*, ISBN 978-

G., Todd, M.D. and Farrar, C.R. (2009b). A mobile-agent-based wireless sensing network for structural monitoring applications, *Measurement Science and Technology*,

**5** 

*Japan* 

Yosuke Fukushima

**Telemetry Data Mining with** 

**SVM for Satellite Monitoring** 

*Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency,* 

The aim of this chapter is to provide readers with a basic knowledge of satellite monitoring and data mining for anomaly detection using a support vector machine (SVM) technique. The author describes the design and implementation of an SVM and an example of the use of the satellite hardware anomaly detection to discover instability in the attitude rate bias of a gyro sensor. This anomaly is caused by a change in the characteristic parameter of the gyro hardware: a statistical parameter related to noise specifications. The detection is

This chapter is divided into three sections: first, the author describes the target satellite and the basic mathematical modelling and formulation of attitude dynamics of the satellite. In the formulation, kinematics and model parameter estimation technique using Kalman filter method is described to provide readers the key parameter; the drift parameters of attitude rate gyro, which are to be dealt with in the following sections in detail. Estimation of unknown parameter of the formulation is also shown using actual telemetry data. This scheme called observers is most popular method for almost every satellite. Second, a brief introduction of the SVM technique is given and followed by a design and implementation of the SVM technique to the gyro bias instability detection. This analysis and calculation are performed using a set of real telemetry data are given. Finally, a software architecture is proposed that will make it easier to migrate SVM software into an onboard computer as a

Although the formulation developed in this chapter is concerned with attitude rate sensors of a particular satellite, this approach can be applied to other types of remote systems; a remote system that is designed to be operated by human operators in a distant site by communicating using telemetry systems. This type of onboard autonomous system monitoring seems to be promising not only in all remote systems that are working at server circumstances such as space or deep underwater but also in some consumer products such

In this section, knowledge of attitude determination of a satellite is given by modelling and analysis of an actual satellite attitude motion in detail. It is necessary to understand meaning

demonstrated using telemetry data that have been sent by an actual science satellite.

**1. Introduction** 

as cars and trains.

step toward realizing onboard autonomy.

**2. Onboard satellite health monitoring** 
