An Enhanced Tracking Algorithm for Distributed Encoding Fiber Bragg Grating Sensor Network

Abstract

Fiber Bragg Grating (FBG) sensor network has attracted more attention in online condition monitoring for the large mechanical equipment. By the efforts of the encoding scheme for sensor nodes, the capacity for the distributed FBG sensor network can be significantly improved. However, due to the increasing number of sensor nodes, the precision of tracking and locating for the FBG sensors has become a bottleneck that should be conquered. In order to realize more accurate and comprehensive condition monitoring for the large mechanical equipment, an enhanced tracking algorithm for distributed encoding FBG sensor network is presented. The novel tracking algorithm uses three classes of progressive intelligent processing approaches, including the improved cycle matching method, the secondary filter intelligent disposal method, and the assistant decision processes method, to conquer the limitations of the traditional tracking algorithm in which the chaos and error results would be caused as the sensor information variations are overlapped. A set of experiments has been conducted and the results demonstrate that the proposed tracking algorithm performs better than the traditional algorithm in location accuracy for the distributed encoding FBG sensor network and can effectively operate in various working conditions of the large mechanical equipment.

Condition Monitoring of Rail Transport Systems: A Bibliometric Performance Analysis and Systematic Literature Review

“…One paper by Zhang et al [ 293 ] brought attention to the increasing number of sensor nodes creating sensor networks ; the authors observed that the tracking and allocation of fiber Bragg sensors in electric sensing devices was becoming a bottleneck in condition monitoring; however, their research was not directly connected to rail transport.…”