We discuss the conditions under which Scan Statistics (SS) can be fruitfully implemented to signal a departure from the underlying probability model that describes the experimental data. It is shown that local perturbations (''bumps'' or ''excesses'' of events) are better dealt within this framework
ORDERED PEAK STATISTICS THROUGH DIGITAL SIMULATION
โ Scribed by BASU, B.; GUPTA, V. K.; KUNDU, D.
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 683 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0098-8847
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โฆ Synopsis
A detailed knowledge of the seismic response time history in the form of the first, second, third, ... largest peak amplitudes is useful to understand the progressive damage in a structure. This information is however not available from the conventionally used response spectra. This paper provides a formulation of the statistics of these higher order peaks by proposing a digitally simulated joint density function for the peaks in a stationary, Gaussian process. A digital experimentation has been done by generating an ensemble of the single-degree-of-freedom oscillator response to several artificial accelerograms, and the corresponding ordered peak distributions have been found to be in close agreement with the predictions based on the formulation in this paper. The peak factors based on the proposed formulation have also been compared with those from the existing formulations based on the Markov theory and on the assumption of peak independence. It has been found that whereas the peak factors from the proposed and Markovian formulations are compatible, the assumption of independence may give reasonable estimates only for the first few orders of peaks.
๐ SIMILAR VOLUMES
A theory based on Markovian principles and transition probability description is presented here to predict the statistics of the ordered peaks in a random process. It takes into account the statistical dependence that exists between the peaks in a single time history. The theory is more general than