Structural Health Fuzzy Classification of Laguna Bridge Based on Hybrid Inspections Results
Authors: Jonnel D. Alejandrino, Ramon P. Flores, Ronnie S. Concepcion II, Vincent Jan D. Almero, Sandy C. Lauguico, Rogelio Ruzcko Tobias
Abstract
Bridge structural health monitoring system (BSHMS) is an aid for systematized decision-making and planning for bridge infrastructure assessment and recondition. One of the critical efforts is to have some criteria to show the current health condition of the bridge based on the inspection results. The conventional way of classification is morphologically and linguistically rated which shows impreciseness and uncertainties in evaluations. The paper proposed a new fuzzy system based on the hybrid (subjective and objective) inspection data results. The optimum value of parameters based on reconstructed data is selected as ambiguous inputs with membership functions using the concept of the statistical distributions and cognitive limitations. The fuzziness of health classification rating is calculated by the fuzzy arithmetic rules inherent in the fuzzy expert system. The proposed Health Classification System, based on hybrid data, yielded a 90 % accuracy in comparison with the conventional inspection method. Thus, the proposed study proved that it can be used for structural health monitoring.