Structural Health Fuzzy Classification of Bridge based on Subjective and Objective Inspections
| Autor: | Ramon Flores, Argel A. Bandala, Elmer P. Dadios, Ronnie Concepcion, Vincent Jan Almero, Justin D. de Guia, Sandy Lauguico, Jonnel Alejandrino |
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| Rok vydání: | 2020 |
| Předmět: |
Fuzzy classification
Computer science Process (engineering) 02 engineering and technology Fuzzy control system computer.software_genre 01 natural sciences Bridge (nautical) Variable (computer science) 0103 physical sciences Management system 0202 electrical engineering electronic engineering information engineering Probability distribution 020201 artificial intelligence & image processing Structural health monitoring Data mining 010301 acoustics computer |
| Zdroj: | 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM). |
| DOI: | 10.1109/hnicem51456.2020.9400054 |
| Popis: | Bridge structural health monitoring (BSHM) and management system is an aid for systematized logistics and management for bridge assessment and recondition. BSHM is inherently formed by visual, advanced, and non-destructive technical inspections. Optimal criterion per parameter is one of the crucial actions in classifying the current condition of bridges. Inconsistency and variation of fundamental parameters makes the process challenging. But there are dominant efforts in determining the preeminent parameters that can only be done after diverse and recursive experiments. On the other side, most prevalent structure condition classification methods are morphologically and linguistically rated, showing impreciseness and uncertainties in evaluations. This paper proposed a new fuzzy system assumed or based on both the objective assessment and subjective approach, along with the optimum value of parameters based on reconstructed data. The best possible fixed and variable parameters of the system's model will be designated as the input for the fuzzy model with membership functions utilizing the concept of the statistical distributions and cognitive limitations. Fundamental arithmetic rules of the fuzzy expert system made the the condition rating of the fuzziness of the system. fuzzy inference systems being one of the established structures for noise tolerance (uncertain and unprecise). The proposed system can be a leading- edge technique for current structural health classification for bridges. |
| Databáze: | OpenAIRE |
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