Defect Detection and Localization of Nonlinear System Based on Particle Filter with an Adaptive Parametric Model

Abstract

A robust particle filter (PF) and its application to fault/defect detection of nonlinear system are investigated in this paper. First, an adaptive parametric model is exploited as the observation model for a nonlinear system. Second, by incorporating the parametric model, particle filter is employed to estimate more accurate hidden states for the nonlinear stochastic system. Third, by formulating the problem of defect detection within the hypothesis testing framework, the statistical properties of the proposed testing are established. Finally, experimental results demonstrate the effectiveness and robustness of the proposed detector on real defect detection and localization in images.

Intelligent Control of Urban Lighting System Based on Video Image Processing Technology

“…In this context, the corresponding lighting systems realize energy conservation and reuse of lighting equipment, and realize the maximum integration of resources [22][23][24]. In the construction of smart city lighting system in the United States, a large number of IOT technologies are applied Such as ZigBee technology, WiFi wireless transmission technology, etc., to a certain extent, it realizes the intelligent layout of smart city lighting system [25][26][27]. The construction of smart city lighting system based on video image processing technology mainly focuses on the optimization and development of video scene recognition technology, but the technology is still relatively immature, and its corresponding anti-interference ability and noise suppression ability are still limited [28][29][30][31].…”