Patent Document ID: 8855852
Application ID: 13782622
Patent Flag: 1

Claim One:
1. A method of monitoring a structure, comprising: a) utilizing an acquisition and recording device and at least one strain sensor to acquire data, the data comprising a plurality of operational parameters x i (t j ) and at least one strain data y(t j ), the operational parameters x i and the strain data y being acquired synchronously over a time series basis (t 1 , t 2 ,. .. , t m ) using the same or different sampling rates; b) building a significant points dataset from the data acquired in a) using a processor; and c) modelling, in the processor, a relationship between the operational parameters x i (t j ) and the strain data y(t j ) using the built significant points dataset to train a non-adaptive prediction functional supervised approximation method, wherein building a significant points dataset comprises: (b1) for each time sample t j , j=1,. .. , m, determining the data modulus ∥ μ (t j )∥ of data vectors μ (t j ) defined as: 
 μ ( t j )=( x 1 ( t j ), x 2 ( t j ),. .. , x n ( t j ); y ( t j )), the data modulus ∥ μ (t j )∥ being calculated as:  μ _ ⁡ ( t j )  = ∑ i = 1 n ⁢ x ~ i ⁡ ( t j ) 2 + y ~ ⁡ ( t j ) 2 with x ~ i ⁡ ( t j ) = 2 · x i ⁡ ( t j ) - x i m ⁢ ⁢ i ⁢ ⁢ n x i ma ⁢ ⁢ x - x i m ⁢ ⁢ i ⁢ ⁢ n - 1 , for ⁢ ⁢ i = 1 , … ⁢ , n ; y ~ ⁡ ( t j ) = 2 · y ⁡ ( t j ) - y m ⁢ ⁢ i ⁢ ⁢ n y ma ⁢ ⁢ x - y m ⁢ ⁢ i ⁢ ⁢ n - 1 and x i min , x i max , y min , y max being respectively the minimum and maximum values for x i and the minimum and maximum values for y in the time series (t 1 , t 2 ,. .. , t m ); (b2) sorting the data vectors μ (t j ), j=1,. .. , m, in N R groups according to the value of their modulus, each group including data with values of modulus within a defined range; (b3) computing within each group the angle α between pairs of vectors and when the angle between a first vector and a second vector is less than or equal to a predetermined angle θ, deleting one of the two vectors.