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Metoda wykrywania uszkodzeń parametrycznych w układach tranzystorowych

100%

Tadeusiewicz M. , Hałgas S. , Sidyk P.

tom Vol. 48, nr 11

31-33

Praca dotyczy badania uszkodzeń wielokrotnych o charakterze parametrycznym w układach tranzystorowych prądu stałego. Przedstawiono nową metodę potestową lokalizacji i identyfikacji uszkodzonych elementów przy ograniczonym dostępie do punktów testowych. W badaniach symulacyjnych uwzględniono silne nieliniowości wprowadzane przez tranzystory bipolarne. Metoda nie stawia bardzo rygorystycznych wymagań w zakresie dokładności pomiarowych. Może być uogólniona na obszerną klasę analogowych układów elektronicznych. Przytoczono przykład liczbowy ilustrujący zaproponowaną metodę i potwierdzający jej skuteczność.

A method for multiple fault diagnosis in DC transistor circuits is developed in this paper. It deals with soft-faults, belongs to the class of simulation after test methods and gets along with strong nonlinearities introduced by the bipolar transistors. The method enables us to identify faulty elements and evaluate their values in the circuits with very limited accessible terminals for excitation and measurement. It does not require very high measurement precision. The method can be generalized to a broad class of electronic circuits. A numerical example illustrates the proposed approach and shows its efficiency.

Sensitivity analysis of multiple fault test and reliability measures in integrated GPS/INS systems

84%

Almagbile A. , Wang J. , Ding W. , Knight N.

tom Vol. 22

25--37

Based on Kalman filtering, multi-sensor navigation systems, such as the integrated GPS/INS system, are widely accepted to enhance the navigation solution for various applications. However, such integrated systems do not always provide robust and stable navigation solutions due to unmodelled measurements and system dynamic errors, such as faults that degrade the performance of Kalman filtering for such integration. Single fault detection methods based on least squares (snapshot) method were investigated extensively in the literature and found effective to detect the fault at either sensor level or integration level. However, the system might be contaminated by multiple faults simultaneously. Thus, there is an increased likelyhood that some of the faults may not be detected and identified correctly. This will degrade the accuracy of positioning. In this paper multiple fault test and reliability measures based on a snapshot method were implemented in both the measurement model and the predicted states model for use in a GPS/INS integration system. The influences of the correlation coefficients between fault test statistics on the performances of the faults test and reliability measures were also investigated. The results indicate that the multiple fault test and reliability measures can perform more effectively in the measurement model than the predicted states model due to weak geometric strength within the predicted states model.

Damage identification of bridge structure model based on empirical mode decomposition algorithm and Autoregressive Integrated Moving Average procedure

59%

Lu W. , Dong J. , Pan Y. , Li G. , Guo J.

tom Vol. 68, nr 4

653--667

Time series models have been used to extract damage features in the measured structural response. In order to better extract the sensitive features in the signal and detect structural damage, this paper proposes a damage identification method that combines empirical mode decomposition (EMD) and Autoregressive Integrated Moving Average (ARIMA) models. EMD decomposes nonlinear and non-stationary signals into different intrinsic mode functions (IMFs) according to frequency. IMF reduces the complexity of the signal and makes it easier to extract damage-sensitive features (DSF). The ARIMA model is used to extract damage sensitive features in IMF signals. The damage sensitive characteristic value of each node is used to analyze the location and damage degree of the damaged structure of the bridge. Considering that there are usually multiple failures in the actual engineering structure, this paper focuses on analysing the location and damage degree of multi-damaged bridge structures. A 6-meter-long multi-destructive steel-whole vibration experiment proved the state of the method. Meanwhile, the other two damage identification methods are compared. The results demonstrate that the DSF can effectively identify the damage location of the structure, and the accuracy rate has increased by 22.98% and 18.4% on average respectively.