A Deflection-Based Bridge Diagnosis Method

Algorithm 2

DIAG_BRIDGE.

INPUT: (𝑉,𝐸,label): a (𝛼,𝛽)-DC graph of a bridge;

𝐻: a set of recent data;

      𝜃: a real number, 0<𝜃<1.

   {

OUTPUT: 𝐹: the collection of all 𝜃-significantly abnormal cliques.

( 1) initially, 𝐹 is empty;

( 2) choose two integers 𝑟 and 𝑙;

( 3) for every pair of checkpoints, 𝑃 and 𝑄,

{

/^∗ sentences 4-5 calculate 𝑟 sample correlated coefficients between 𝑃 and 𝑄; ∗

(4) randomly select 𝑟 pairs of length-𝑙 sequences from 𝐻, one for 𝑃, and the other for 𝑄;

(5) for each pair of selected sequences, calculate a sample correlated coefficient;

   /^∗ sentence 6 calculates the frequency at which these 𝑟 sample correlated coefficients fall in

        𝐼_𝐻(𝑃,𝑄); ∗

(6) num ← the number of these 𝑟 sample correlated coefficients that fall in 𝐼_𝐻(𝑃,𝑄);

   /^∗ sentence 7 performs diagnosis; */

(7) if num/𝑟<𝛼−𝜃, then add 𝑃 and 𝑄 to 𝐹;

  }

  }.