### Abstract

Language | English |
---|---|

Pages | 528-533 |

Number of pages | 5 |

Journal | Smart Materials and Structures |

Volume | 10 |

Issue number | 3 |

DOIs | |

Publication status | Published - 2001 |

### Fingerprint

### Keywords

- point selction
- mutual information
- damage detection

### Cite this

*Smart Materials and Structures*,

*10*(3), 528-533. https://doi.org/10.1088/0964-1726/10/3/315

}

*Smart Materials and Structures*, vol. 10, no. 3, pp. 528-533. https://doi.org/10.1088/0964-1726/10/3/315

**Measurement point selection in damage detection using the mutual information concept.** / Trendafilova, I.; Heylen, W.; Van Brussel, H.H.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Measurement point selection in damage detection using the mutual information concept

AU - Trendafilova, I.

AU - Heylen, W.

AU - Van Brussel, H.H.

PY - 2001

Y1 - 2001

N2 - The problem for measurement point selection in damage detection procedures is addressed. The concept of average mutual information is applied in order to find the optimal distance between measurement points. The idea is to select the measurement points in such a way that the taken measurements are independent, i.e. the measurements do not 'learn' from each other. The average mutual information can be utilized as a kind of an autocorrelation function for the purpose. It gives the average amount of information that two points 'learn' from each other. Thus the minimum of the average mutual information will provide the distance between measurement points with independent measurements. The idea to use the first minimum of the average mutual information is taken from nonlinear dynamics. The proposed approach is demonstrated on a test case. The results show that it is possible to decrease significantly the number of measurement points, without decreasing the precision of the solution.

AB - The problem for measurement point selection in damage detection procedures is addressed. The concept of average mutual information is applied in order to find the optimal distance between measurement points. The idea is to select the measurement points in such a way that the taken measurements are independent, i.e. the measurements do not 'learn' from each other. The average mutual information can be utilized as a kind of an autocorrelation function for the purpose. It gives the average amount of information that two points 'learn' from each other. Thus the minimum of the average mutual information will provide the distance between measurement points with independent measurements. The idea to use the first minimum of the average mutual information is taken from nonlinear dynamics. The proposed approach is demonstrated on a test case. The results show that it is possible to decrease significantly the number of measurement points, without decreasing the precision of the solution.

KW - point selction

KW - mutual information

KW - damage detection

UR - http://dx.doi.org/10.1088/0964-1726/10/3/315

U2 - 10.1088/0964-1726/10/3/315

DO - 10.1088/0964-1726/10/3/315

M3 - Article

VL - 10

SP - 528

EP - 533

JO - Smart Materials and Structures

T2 - Smart Materials and Structures

JF - Smart Materials and Structures

SN - 0964-1726

IS - 3

ER -