Chain State Monitoring for a Heavy Scraper Conveyor Using UWB-Based Extended Kalman Filter Technique With Range Constraint Selection Method
Yilian Hua, Zhencai Zhu, Gongbo Zhou, Gang Shen
Abstract
Ultrawideband (UWB) is a promising wireless radio frequency technology with centimeter-level ranging capabilities. In view of this feature, this article describes a new approach to condition monitoring for the chain of scraper conveyors. An extended Kalman filter (EKF) technology based on UWB is used to locate and track the offset of the two ends of the scraper blades and achieve the purpose of monitoring the health condition of the chain. In addition, considering the presence of environmental noise and the nonline-of-sight factors, the new positioning algorithm uses the more accurate UWB ranging information computed from the range constraint selection method (RCSM) in conjunction with EKF and motion model to select and improve measured values and, finally, to reduce the measurement errors and improve the positioning accuracy. Compared with the results from the weighted least-squares (WLSs) method and EKF estimated without RCSM, the proposed UWB-based EKF technique with RCSM performs better both in accuracy and stability. The experimental results obtained from the proposed method are presented to show good and stable monitoring performance both in normal working conditions and the case of the tilting blade.