# An Intelligent Warning Method for Diagnosing Underwater Structural Damage
## 3 Experiment and Result Analysis
### Triangle Algorithm  
The accuracy of extracting feature parameters depends on the optimal generation criteria, including the image gray level, \(g\), the generative step length, \(d\), and the generative angle, \(\theta\). Therefore, it is crucial to optimize the factor to obtain accurate and effective feature parameters. Generally, the orthogonal test method (OTM) and full test method (FTM) are used to establish generative criterion. However, OTM leads to the absence of a partial criterion and FTM reduces detection efficiency. Therefore, a new triangulation algorithm used for the confirming of generative criterion is presented in this paper. Figure 5 is the diagram of algorithm.  
1. The initial range of the factor of the generative criterion is determined according to the properties of the micro-damage image.
2. Confirm the generative angle, \(\theta\), by the theory of image rotation invariant. In Figure 5, the _sequence A_ is he generative step length, \(d\), \(g_{1}\)-\(g_{n}\)_n_ is the _sequence B_ image gray level, \(g\), \(g_{1}\)-\(g_{n}\).
3. The sequence A is linked to the sequence B, and \(\theta\) is then joined to sequence A and sequence B, respectively.
4. Extract all \(d_{n}\)-\(\theta\)-\(g_{t}\) combinations. Then, a triangular combination can form.  
The algorithm was validated based on the underwater micro-damage diagnosis system. Based on the comparative analysis, the unique advantages of the triangulation algorithm were proven.  
In order to ensure the features of the image rotation invariant, the average values directions of \(0^{\circ}\), \(45^{\circ}\), \(90^{\circ}\), and \(135^{\circ}\) were selected as the generative angle, \(\theta\). Figure 6 is the variations' form of \(\theta\).  
Figure 4: Acquisition system.  
Figure 5: Algorithm.  
Figure 6 shows the difference in the characteristic parameters of micro-damage images. The different directions are small. Therefore, the generation angle, \(\theta\), of the generation criterion was determined.  
The initial range of the generated standard factor was obtained based on the characteristics of the micro-damage image:  
(1) Generative angle, \(\theta\): The average of directions of \(0^{\circ}\), \(45^{\circ}\), \(90^{\circ}\), and \(135^{\circ}\).  
(2) Image gray level: \(g_{t}=2^{m+2}\), among them, \(t=m+2\), \(t\) is taken as the integer of [1,6].  
(3) Generative step length, \(d\): Take the integer of [1,6].  
The combination form of the generation standard, \(dn\)-\(\theta\)-\(gt\), was obtained by the triangulation algorithm. It has a total of \(n\times t=n\times(m+2)=36\) groups. The OTM requires determination of the values of the two construction factors in advance to obtain the combined form. If the two construction factors select \(g\) and \(d\), the \(d\)-\(\theta\)-\(g\) forms a total of \(1\times 1\times 4=4\) groups. Additionally, the FTM does not specify the range of variation of any factor. If the values of \(d\) and \(g\) are the same as the triangulation algorithm, the \(d\)-\(\theta\)-\(g\) forms a total of \(6\times 6\times 4=144\) groups. Experimental verification and comparison results showed that this method can efficiently obtain all the generation criteria of micro damage. The proposed triangulation algorithm obtained the appropriate combination form based on the image properties and effectively improved the detection efficiency.