Papers by Keyword: Health Diagnosis

Abstract: In order to evaluate the health condition of the tunnel in South China and give advices on reinforcement and maintenance scheme, a post-earthquake health diagnosis method is presented. After a comprehensive investigation on failure modes of tunnel, a four-level ranking method and a index system for post-earthquake health diagnosis of highway tunnel are proposed. Besides, analytical hierarchy process (AHP) is introduced into for determining the post-earthquake health diagnosis mode. Case study manifests the validity of the proposed method, which can provide valuable guide to the post-earthquake health diagnosis and relief work.

Abstract: In order to achieve the quantitative health diagnosis of operational tunnel, established the health diagnosis system and the evaluating criterion based on the mechanism of tunnel disease, used the weighted average operator to obtain comprehensive evaluation results, applied the asymmetric proximity to decide the grade of tunnel structure health, thus build a complete fuzzy comprehensive evaluation model. Finally, by taking the example of Lilong tunnel located at LiuHe Express way, and made analysis and evaluation to its structure health status. The results show that the improved grey relevancy method to determine the index weight can avoid the subjective arbitrariness and improve the reliability of the evaluation model, making a decision and analysis by asymmetric proximity insures the diagnosis results more correspond with the objective reality.

Abstract: By means of inductive analysis the health diagnosis weighting methods in engineering, this paper discusses the basic principle, advantages, disadvantages and applicable scope of weighting methods. On the basis, combining with multi-level, multi-standard and multi-factor characteristic of hydraulic metal structures health diagnosis, the methods of AHP, information gain, information diffusion and improved entropy are studied, which are applicable to hydraulic metal structures health diagnosis weighting. Based on fuzzy theory, the fuzzy multi-level comprehensive weighting method is put forward and studied, which combined both subjective and objective method advantages and its complementary. In addition, it provides the necessary theory foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

Abstract: To overcome the huge difficulties in constructing an accurately finite element model in health diagnosis of bridge, this paper presented an improved diagnosis method via exponential weighted moving average (EWMA) control chart. Firstly the characteristic of the live-load effect of main girder strain in a bridge was analyzed as a theoretical basis of the proposed strategy. Then wavelet analysis was employed to extract the live-load effect of strain from the total measurement as sensitive feature for structural health diagnosis. Finally the EWMA control chart was designed to complete the structural health diagnosis of bridge, in which the multi-stage control limits are estimated by reliability analysis. The results from application in a concrete cable-stayed bridge show significant effectiveness of the proposed method in health diagnosis of bridge.

Abstract: In order to diagnose the health state of Aircraft effectively, a new method based on ARMA Model and probabilistic neural network(PNN) is proposed in this paper. First, an ARMA model is built using the original acoustic emission signal of aircraft crucial components, then use the autoregressive approximation theory to estimate model parameters, and order of the model is calculated according to Akaike Information Criterion(AIC). Use the autoregressive parameters to build feature vectors, then the probabilistic neural network is used to carry out the recognition of these feature vectors, and the health state of aircraft crucial components is effectively diagnosed. After the application on certain type of real aircraft, this method is proved to be capable of detecting the fatigue crack on crucial structural components. And we can conclude that the method is an effective way to carry out aircraft health diagnosis.

Abstract: In order to diagnose the health status of aircraft effectively, a health diagnosis method based on D-S evidence theory is proposed. Firstly, this method apperceives the healthy information of a real aircraft stabilizer with real time by using AE(Acoustic Emission, AE) detecting system. Secondly, use the wavelet transform to extract feature of the AE signal, including three characteristics of maximum value (MA), singular value (SVD), standard deviation (STD) to set up characteristic vector, then using GRNN and BP neural network to classify the characteristic vector. Finally, D-S evidence theory is used for decision reasoning. Therefore, The Health State of aircraft can be diagnosed. Experiments show that the monitor has good performance to recognize and diagnose the fatigue crack of aircraft structural parts, which is proposed to be effective.