Abstract: The present invention relates to an intelligent fiber optical distributed acoustic sensing (FODAS) system and method based on an artificial intelligence (AI) chip, belonging to the field of distributed optical fiber sensing technologies. The system comprises a light source, a modulator, an optical amplifier, a sensing part, a data processor, a photoelectric detector, and an alarm unit, where the data processor is specifically an AI chip; the light source, the modulator, the optical amplifier and port a of a circulator are connected in sequence, port b of the circulator is connected to an optical fiber, port c of the circulator is connected to the photoelectric detector, an output end of a detector is connected to the data processor, an output end of the data processor is connected to the alarm unit; and the data processor receives external acoustic signals and extracts amplitude and frequency features of the external acoustic signals to identify the type.
Abstract: A fully distributed magnetic adsorption multi-parameter sensing cable, which is configured to be installed on the wall of a metal pipeline, includes an outer sheath, a sensing component arranged in the outer sheath, and a fully distributed magnetic adsorption reinforcement (FDMAR) arranged in the outer sheath and on a peripheral side of the sensing component. The outer sheath is attached to the wall of the metal pipeline by the FDMAR. A magnetic adsorption force between the FDMAR and the wall of the metal pipeline is able to be adjusted by changing the size of the FDMAR and the distance between the FDMAR reinforcement and the wall of the metal pipeline. The fully distributed magnetic adsorption multi-parameter sensing cable has the advantages of good adsorption effect and high sensitivity.
Type:
Grant
Filed:
September 30, 2020
Date of Patent:
December 28, 2021
Assignees:
Zhongtian Power Optical Cable Co., Ltd, JIANGSU ZHONGTIAN TECHNOLOGY CO LTD, Sichuan Guangsheng IOT Technology Co., Ltd.
Inventors:
Yunjiang Rao, Bing Han, Hongjian Guan, Qiang Li, Ming Li, Zengling Ran, Jiping Xue, Shuhong Xie, Cangping He